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What is Speech To Text?

What is speech to text?

Speech to text is a speech recognition software that enables the recognition and translation of spoken language into text through computational linguistics. It is also known as speech recognition or computer speech recognition. Specific applications, tools, and devices can transcribe audio streams in real-time to display text and act on it.

How does speech to text work?

Speech to text is software that works by listening to audio and delivering an editable, verbatim transcript on a given device. The software does this through voice recognition. A computer program draws on linguistic algorithms to sort auditory signals from spoken words and transfer those signals into text using characters called Unicode. Converting speech to text works through a complex machine learning model that involves several steps. Let's take a closer look at how this works:

• When sounds come out of someone's mouth to create words, it also makes a series of vibrations. Speech to text technology works by picking up on these vibrations and translating them into a digital language through an analog to digital converter.
• The analog-to-digital-converter takes sounds from an audio file, measures the waves in great detail, and filters them to distinguish the relevant sounds.
• The sounds are then segmented into hundredths or thousandths of seconds and are then matched to phonemes. A phoneme is a unit of sound that distinguishes one word from another in any given language. For example, there are approximately 40 phonemes in the English language.
• The phonemes are then run through a network via a mathematical model that compares them to well-known sentences, words, and phrases.
• The text is then presented as text or a computer-based demand based on the audio’s most likely version.

What are the types of speech to text technology?

There are two main types of speech to text technology:

• Speaker-dependent : Mainly used for dictation software.
• Speaker-independent : Often used for phone applications.

These two speech recognition systems rely on software and services to function adequately, with the main type being built-in dictation technology. Many devices now have built-in dictation tools, such as laptops, smartphones, and tablets

What are the applications of speech to text?

Speech to text has quickly transcended from everyday use on phones in homes to applications in industries like marketing, banking, and medical. Speech recognition applications reveal how voice to text technology can increase the efficiency of simple tasks and extend to tasks that humans have traditionally performed.

Call analytics and agent assist

Using a tool like Transcribe Call Analytics allows you to extract actionable insights from customer conversations quickly, enabling improvements in customer engagement and increasing agent productivity.

Media content search

Amazon transcribe converts audio and video assets into searchable archives. It also allows users to improve the reach and accessibility of content by generating localized subtitles in combination with  Amazon Translate .

Marketing is one of the leading industries to draw on speech to text through media content search. The introduction of voice-search allows for information about trends in data and consumer behavior for marketers.

For example, speech recognition provides information on people's accents and vocabulary, interpreting age, location, and other important demographics. Speaking is also a much more conversational search mode, allowing marketers to incorporate conversational keywords to stay ahead of trends.

Media subtitling

Amazon transcribe can also capture meetings and conversations through the digital scribe function, improving productivity, accessibility, and streamlining important notes.

Clinical documentation

Amazon Transcribe Medical  is a tool for medical professionals to quickly and efficiently record clinical conversations into electronic health record systems for analysis. For example, in banking, speech to text is used through voice-activated customer service. In the healthcare sector, speech to text helps improve efficiency by providing immediate access to information and inputting data.

Why should you use speech to text?

Like all forms of technology, speech to text has many benefits that help us improve daily processes. These are some of the main advantages of using speech to text:

• Save time : Automatic speech recognition technology saves time by delivering accurate transcripts in real-time.
• Cost-efficient : Most speech to text software has a subscription fee, and a few services are free. However, the cost of the subscription is far more cost-efficient than hiring human transcription services.
• Enhance audio and video content : Speech to text capabilities mean that audio and video data can be converted in real-time for subtitling and fast video transcription.
• Streamline the customer experience : By drawing on natural language processing, the customer experience is transformed through ease, accessibility, and seamlessness.

What are the limitations of speech to text?

New technologies like speech to text don't come without imperfection, and these are some of the main limitations of speech to text:

• It isn't perfect : While dictation technology is a powerful tool, it is still in its early days,which means there are some gaps in its overall performance. Because it produces verbatim text only, you can end up with an inaccurate or awkward transcript or missing specific quotations.
• Requires human input : Because speech to text lacks complete accuracy, some human edits to the speech data are required for optimal usage.
• Requires clean recordings : To get a quality transcript from voice recognition software, you need to ensure the recorded audio is clear and intelligible. This means there needs to be no background noise, adequate pronunciation, no accents, and one person speaking at a time. You also need to provide voice commands for punctuation.

How to choose free speech to text software vs. paid?

Free speech to text software is helpful if you are on a limited budget. However, if you want to transcribe a large volume of audio to text you will need more robust software. Paid speech to text software is often more accurate, faster, and has added features and support.

Most free speech to text software:

• Do not offer quality technical support.
• Do not offer the greatest speed or accuracy.
• Have a limited capacity.
• Require a lot of extra editing on your part.

How to choose the best speech to text software?

With so many options available, choosing the best speech to text software can be challenging. Use the checklist below to assess the different speech to text software and make the best choice for you:

• No additional software is required - The most accessible speech to text software relies on an internet connection rather than additional software.
• Accuracy level is guaranteed - All speech to text services offer a degree of certainty. Some services have a greater focus on transcription, which ensures extra accuracy.
• Multi-language support - If you need multi-language support, you will need to choose a speech to text software that meets your language needs.
• App compatibility - Some speech to text services can be added to apps, which is important if you wish to use the software across multiple platforms.

How to use Amazon Transcribe for speech to text?

Using automatic speech recognition (ASR), Amazon Transcribe converts speech to text quickly and accurately. Amazon Transcribe offers a range of accessible tools for various uses including call analytics, medical transcriptions, subtitling, and generating metadata for media assets. To get started, simply sign up for a free AWS account and start transcribing with the free speech to text option today.

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What is speech-to-text?

Speech-to-text, or automatic speech recognition (ASR), technology has been around for a while, but it is only recently that it has gained widespread adoption. ASR allows users to speak commands and control their devices using their voice, making it a popular choice for virtual assistants, captioning and transcription, customer service, education, medical documentation, and legal documentation. According to Forrester's survey , many information workers in North America and Europe use voice commands on their smartphones at least occasionally, with the most common use being texting (56%), searching (46%), and navigation/directions (40%). However, there are still challenges that need to be addressed in order for this technology to reach its full potential. 

In this article, we will explore the different methods of speech-to-text and how it is used in various applications, including transcription services, voice recognition software, and accessibility tools. We'll also take a look at the future of speech-to-text and see how this technology is likely to continue to improve and expand in the coming years. So, let's dive in and see what makes speech-to-text such a powerful tool for businesses and individuals alike.

How speech-to-text technology works 

Speech-to-text technology is a type of natural language processing (NLP) that converts spoken words into written text. It is used in a variety of applications, including voice assistants, transcription services, and accessibility tools. Here is a more detailed explanation of how speech-to-text technology works:

Sound conversion

The first challenge in speech-to-text technology is that sound is analog, while computers can only understand digital inputs. To convert sound into a digital format that computers can understand, a microphone is used. The microphone converts sound waves into an electrical current, which is then converted into voltage and read by a computer.

Frequency isolation

The next step in the process is to isolate individual frequencies from the sound input. This is done using a technique called Fast Fourier Transform (FFT), which converts the sound input into a spectrogram. A spectrogram is a visual representation of sound, with time on the X-axis, frequencies on the Y-axis, and intensity represented by brightness.

Phoneme recognition 

It’s the process of identifying the basic building blocks of speech, known as phonemes. This is a crucial step in speech-to-text technology because phonemes are the foundation upon which words are built. There are several different approaches to phoneme recognition, including statistical models like the hidden Markov model and machine learning systems like neural networks.

Neural networks are a type of machine learning system that is made up of interconnected nodes that can adjust their weights based on feedback. A neural network consists of layers of nodes that are organized into an input layer, an output layer, and one or more hidden layers. The input layer receives data, the hidden layers perform transformations on the data, and the output layer produces the final result. Every time the neural network receives feedback, it adjusts the weights of the connections between the nodes to improve its performance.

One advantage of neural networks is that they can adapt to large variations in speech, such as different accents and mispronunciations. However, they do require a large amount of data to be set up and trained, which may be a limitation for some applications. In contrast, statistical models like the hidden Markov model are less data-hungry, but they are unable to adapt to large variations in speech. As a result, it is common to use both types of models in speech-to-text technology, with the hidden Markov model being used to handle basic phoneme recognition and the neural network handling more complex tasks.

Word analysis  

It’s the process of analyzing the sequence of phonemes that make up a word in order to identify the intended meaning. This is done using either a language or an acoustic model.

The language model takes into account the context of the word, as well as the frequency of different phoneme combinations in the language being used. For example, in English, the phoneme "m" is never followed by an "s." Therefore, if the language model encounters the sequence "ms," it will consider it to be an error and attempt to correct it based on the context and the likelihood of different phoneme combinations.

The language model is an important part of speech-to-text technology because it allows the system to understand the meaning of words and sentences. By analyzing the sequence of phonemes and taking into account the context, the language model can determine the intended meaning of spoken words and produce the corresponding written text.

The acoustic model is a statistical model that maps the acoustic features of speech to the corresponding words or phonemes. The acoustic model is trained on a large dataset of audio recordings and the corresponding transcriptions, and it uses this data to learn the patterns and features that are characteristic of the language being used.

During the STT process, the audio input is analyzed by the acoustic model, which produces a sequence of probability scores for each possible word or phoneme. The sequence of scores is then fed into a language model, which takes into account the context and the likelihood of different word combinations to produce the final transcription.

There are several different types of acoustic models, including hidden Markov models (HMMs) and deep neural networks (DNNs). HMMs are statistical model that consists of states and corresponding evidence, and they are commonly used for speech recognition because they are computationally efficient and relatively easy to train. DNNs are a type of machine learning model that consists of layers of interconnected nodes, and they are able to adapt to large variations in speech. DNNs are more data-hungry and require more computational resources to train, but they tend to perform better than HMMs on many speech recognition tasks.

Which model is better or more common for a given language depends on a variety of factors, including the complexity of the language, the amount of data available for training, and the resources available for training and running the model. In general, DNNs tend to perform better on a wide range of tasks, but they may not be the best choice for all languages or situations.

Final transcript

Text output is the final step in converting spoken words or text from one language to another using speech-to-text technology. It involves displaying the translated text on a screen or saving it to a file.

What are STT APIs and their advantages? 

API (Application Programming Interface) is a set of rules and protocols that allows different software systems to communicate with each other. In the context of speech-to-text applications, an API is a set of programming instructions that allows developers to access and use the STT capabilities of a service or platform in their own applications.

There are several different types of voice recognition APIs available, including cloud-based APIs and on-premises APIs. Cloud-based APIs are hosted by a third-party provider and accessed over the internet, while on-premises APIs are installed on a local server and accessed within an organization's network.

Speech-to-text APIs offer plenty of advantages for individuals and businesses:

Increased productivity : Allows users to input text quickly and efficiently using their voice, rather than typing on a keyboard or touchpad. This can save time and increase productivity, especially for tasks that involve a lot of text input.

Improved accessibility : Can be used to provide accessibility features such as live captions and subtitles, which can be helpful for individuals with hearing impairments or learning disabilities.

Enhanced customer experience : Speech-to-text applications can provide various manipulations with recognized and transcribed text, for example, summarization . By getting a quick summary of customer feedback businesses can identify common issues, for example. 

Greater flexibility : STT APIs can be accessed from any device with an internet connection, allowing users to input text using their voice from anywhere.

Cost savings : One of the major benefits for businesses is cost savings. By automating text input tasks, businesses can reduce or eliminate the need for manual transcription services, which can be costly and time-consuming. Additionally, it can help businesses streamline their processes and increase efficiency.

Improved accuracy : Advanced natural language processing algorithms have a high level of accuracy in transcribing spoken words, which can help reduce errors and improve the quality of the resulting text.

Best speech-to-text API applications

There are many speech-to-text (STT) application programming interfaces (APIs) available on the market, and the best one for you will depend on your specific needs and preferences. Here are some popular STT APIs that are widely used and well-regarded by experts:

• Google Cloud Speech-to-Text API : Use a powerful API to convert speeches into texts accurately with the help of Google Cloud’s Speech-to-Text solution known for its high accuracy and wide range of customization options. It offers an excellent user experience by transcribing your speech with accurate captions.
• IBM Watson Speech to Text API : IBM Watson Speech to Text offers AI-powered transcription and speech recognition solutions. It enables accurate and fast speech recognition in different languages for various use cases, such as customer self-service, speech analytics, agent assistance, and more.
• Microsoft Azure Speech Services : Use a powerful API to convert speeches into texts accurately with the help of Google Cloud’s Speech-to-Text solution. It offers an excellent user experience by transcribing your speech with accurate captions. It also helps improve your services through the insights taken and transcribed from your customer interactions.
• Amazon Transcribe : Amazon Transcribe is a big cloud-based automatic speech recognition platform developed specifically to convert audio to text for apps. It is available for use on a variety of platforms, including Windows, Mac, and mobile devices.
• OneAI is a language AI service that offers product-ready APIs and pre-trained models for developers. It allows developers to access speech-to-text and audio-intelligence capabilities in a single API call, enabling them to process audio and video into structured data for various purposes such as generating summaries and transcripts, and detecting sentiments and topics.

Use cases of speech-to-text applications

There are many potential use cases for speech-to-text technology. Some of the most common use cases include:

Automated dictation

If you're a content creator, writer, or anyone who needs to type long-form text, STT APIs can be a huge help. You can dictate your words and produce written text, saving time and effort.

Voice control

Speech-to-text can be used to enable voice control of various applications, such as virtual assistants or smart home devices. By issuing voice commands, users can easily interact with these devices and perform a wide range of tasks without having to type or use other input methods.

Medical transcription

In the medical field, this technology can be used to transcribe medical reports, notes, and other documents. This can help to reduce the workload for medical professionals and improve the accuracy of patient records

Translation

You can translate spoken words into different languages, which can be particularly useful for people who are traveling or working with people who speak different languages.

Voice biometrics

It’s the process of verifying the identity of a user based on their voice and also can be a task for voice recognition applications. This can be used to enable secure authentication for applications such as banking or online services.

Students with learning disabilities or language barriers can use the benefits of STT applications by getting real-time transcriptions of lectures or other educational materials. This can make learning more accessible and inclusive for all students.

Emotion recognition

Speech-to-text can also be used to analyze certain vocal characteristics to determine what emotion the speaker is feeling. Paired with sentiment analysis, this can reveal how someone feels about a product or service.

Limitations and future of speech-to-text

Like all technology, speech-to-text technology has its limitations. Some of the main limitations include:

Accurate transcription relies on clear speech : voice recognition systems are more likely to produce accurate transcriptions when the spoken words are clear and easily understood. If the speech is distorted or difficult to understand, the accuracy of the transcription may suffer.

Accents and dialects : Voice recognition systems are typically trained on a particular accent or dialect of a language. If the speaker has a different accent or dialect, the accuracy of the transcription may be lower.

Problems with context understanding : STT systems may struggle to understand the context in which words are being used, which can lead to incorrect transcriptions or translations.

Significant computing resources are required : Developing and maintaining voice recognition systems can be resource-intensive, as they require large amounts of data and computing power to train and operate.

Despite these limitations, the future of this technology looks bright. The speech-to-text industry has seen significant growth in recent years, with the global market value expected to reach $28.1 billion by 2027. The increased demand for this technology has led to the development of advanced capabilities such as punctuation, speaker diarization, global language packs, and entity formatting. One major breakthrough in the industry is the introduction of self-supervised learning, which allows STT engines to learn from unstructured data on the internet, giving them access to a wider range of voices and dialects and reducing the need for human supervision.

Universal availability will make ASR accessible to everyone, while the collaboration between humans and machines will allow for the organic learning of new words and speech styles. Finally, responsible AI principles will ensure that ASR operates without bias.

Speech-to-text technology has come a long way in recent years, and its capabilities continue to expand with the development of self-supervised learning and the integration of natural language understanding (NLU) . These advancements have enabled speech-to-text systems to learn from a wide range of unstructured data and improve their accuracy in a variety of languages and accents. As a result, STT technology is being utilized in an increasingly diverse range of industries, from healthcare and finance to communications and customer service.

OneAI creates 93% accurate speech-to-text transcriptions and suggests a wide range of Language Skills (use-case ready, vertically pre-trained models) like summarization , proofreading , sentiment analysis , and many more. Just check our Language Studio and pick those which will increase the efficiency of your business. 

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Understanding Speech to Text in Depth

Have you ever transcribed an interview before? Or seen an individual with disabilities use voice recognition software to control their devices and create text using their voice commands?

If yes, then you have directly experienced the impact of speech to text technology . Better known as STT, these tools help convert audio into written text. It works with a combination of artificial intelligence, deep learning, and computational linguistics.

To give you another real-life example of speech to text, YouTube features a ‘Closed Captions’ option that enables the live transcription of the dialogue happening on the video in real-time. 

There are several use cases where voice to text comes in handy, including the dictation processes during meetings, transcribing important interviews, and much more.

In this blog, we’ll go through the evolution of speech to text, benefits, applications, and what the future of the technology looks like.

Table of Contents

Need for speech to text, 1. enhanced accessibility through speech recognition, 2. improved productivity, 3. hands-free operation through spoken words, 4. multitasking through voice commands, 5. language support through google speech recognition, 1. multilingual and cross-language capabilities, 2. enhanced customization and personalization, 2. integration with virtual and augmented reality, 3. expanded use in healthcare, 4. incorporation into smart assistants and iot devices, does murf have a speech to text, evolution of speech to text.

Speech recognition has always been under constant improvement since the 1950s. In fact, Bell Laboratories pioneered the world’s first speech recognition setup called AUDREY, which could recognize spoken numbers with almost 99% accuracy. However, the system was too bulky and consumed copious amounts of power.

In 1962, IBM innovated the niche with Shoebox, a speech recognition system that was able to recognize both numbers and simple mathematical terms. On a parallel timeline, the Japanese scientists were hard at work creating phoneme -based speech recognition technologies and speech segmenters.

This was when Kyoto University achieved a breakthrough in speech segmentation, allowing computers to ‘Segment' one sentence into a new line of speech for the subsequent tech to work on sound identification.

It wasn’t until HARPY from Carnegie Mellon came around in the 1970s that computers could recognize sentences from just over a 1,000-word vocabulary. The system was the first to use Hidden Markov Models, a probabilistic method that laid the foundation for the modern-day ASR.

The 1980s saw the first speech to text tool that leveraged IBM’s transcription system, Tangora. These tools were viable and usable and would then be polished to become the modern-day speech recognition software.

The fact that people around the world needed to generate transcripts at scale and fast led to the development of speech to text software.

Today, their use has expanded into other utilities as well, serving to provide live translations of language and aiding people with disabilities to participate in the online world equitably.

The speech to text process can be explained in five simple steps:

Vibration analysis: When a person speaks, the voice vibrations are first analyzed by STT software.

Phoneme identification: The software then identifies the phonemes in the input sound.

Phoneme-sentence correlation: The identified phonemes are then run through a mathematical algorithm to create sentences.

Linguistic algorithmic conversions: The phonemes are put together to form words and put into coherent sentences.

Output in the form of Unicode characters: The words are now displayed as Unicode characters.

Benefits of Speech to Text

Speech to text provides tremendous advantages to users:

Speech to text is an exemplary accessibility tool for people with mobility or visual disabilities to express themselves. Spoken language can be converted into text automatically, allowing them to take part in threads and discussions on, say, social media platforms.

Speech to text is also an excellent tool to use for enhancing productivity at work that involves exhaustive transcribing processes. The entire workflow can be automated to convert audio to text, clean the text, and then push it further for translation or proofreading.

Hands-free keyboard operation is another productivity enhancement that speech to text provides to users. Professionals can leave their desks and dictate meeting notes or instructions or type a letter using speech to text on popular software like MS Word.

Speech to text allows users to tackle multiple tasks at the same time. For example, while using STT tools for dictating onboarding instructions for a new hire, a professional can continue to read through the files that have been closed or need to be handed over.

Speech to text enables professionals to type in another language using speech. There are tools that take input speech recognition in one language and output the text in a different language selected by the user. It helps prevent errors in sensitive documents for international businesses.

Future of Speech to Text

In the near future, innovations in speech to text would unravel the improved potential of the technology across a variety of use cases:

Polyglot capabilities are set to emerge with speech to text tools promptly converting one language into written text in a second language. In the next step, the typed text in L2 can be converted into spoken audio again, achieving cross-language capabilities.

Currently, speech to text technologies feature a wide range of voice and language selections. In the future, there is potential to offer better voice modulation, auto punctuation, and customization capabilities to users for enhanced branding and user experience.

Speech to text can be extensively employed in VR and AR modules for simulating conversations with AI assistants or agents. It can prove to be a highly effective tool for corporate training , skill-building, and scenario simulations.

Speech to text has the potential to provide enhanced functionality to administrative tasking in the healthcare sector. It can help doctors quickly and efficiently provide prescriptions to patients and also help medical researchers take notes on a subject as they continue to study.

Speech to text is already finding expanded utility in voice assistants that work by recognizing speech and following through with voice commands. This capability can be further expanded into IoT beyond domestic use into specialized operations as well (like industrial operations).

Murf Studio is primarily a versatile platform that provides high-quality AI voices for text to speech conversions. While the platform doesn’t offer a standalone speech to text module, users can still convert audio to script using Murf’s AI voice changer feature through the following steps:

Login to the Murf Studio dashboard and select AI voice changer from the left sidebar.

Select a recorded audio or video to upload to the platform.

Select the language that your audio file is recorded in.

Once you see the transcribed text appear on the dashboard from your audio, you can proceed to download the text script from the interface. If required, you can apply customizations to the text here as well.

Click on the context menu option beside the text script and select “Download Script.”

Murf Studio allows you to download the text script in a variety of formats. You can also translate the script into 20+ languages available on the platform.

Speech to Text: More Than Just an Accessibility Enhancer

Speech to text tools are a boon for people who require tasking assistance. However, these tools can do more than just assistive tasks. Professionals actively employ STT to achieve higher levels of productivity at work; people also use it in their daily lives to interact with voice assistants.

Speech to text tools have become extremely accessible today, with advanced online platforms available aplenty. The simplicity in ease of use and quick transcriptions they provide have made it more inclusive for the populace.

What is STT technology, and how does it work?

Speech to text tools convert spoken words into text. They work by identifying sounds in a recording and converting them into corresponding text.

How accurate is speech to text?

Modern-day speech to text tools are extremely accurate as they work with expanded voice databases that allow for accurate transcriptions.

What are the objectives of speech to text?

Speech to text is purposed to convert spoken words and phrases into typed text with a view to enhance accessibility and productivity.

How is AI used in speech to text?

AI enables predictive and voice typing when using dictation methods on software like MS Word.

What applications use speech to text technology?

Daily-use electronics like Amazon’s Alexa or the voice assistants on your phone use speech to text technology.

Can speech to text handle multiple languages?

Yes, speech to text software can convert between languages once a text transcript is available.

How secure is speech to text technology?

Depending on the software you select, the degree of security varies in STT. 

Can speech to text technology be used for real-time transcription?

Yes, YouTube and other video platforms leverage STT for real-time caption generation.

You should also read:

Top 10 Speech to Text Software in 2024

How Speech Recognition is Changing Language Learning

Future of AI in Speech Recognition 

Speech to text

An AI Speech feature that accurately transcribes spoken audio to text.

Make spoken audio actionable

Quickly and accurately transcribe audio to text in more than 100 languages and variants. Customize models to enhance accuracy for domain-specific terminology. Get more value from spoken audio by enabling search or analytics on transcribed text or facilitating action—all in your preferred programming language.

High-quality transcription

Get accurate audio to text transcriptions with state-of-the-art speech recognition.

Customizable models

Add specific words to your base vocabulary or build your own speech-to-text models.

Flexible deployment

Run Speech to Text anywhere—in the cloud or at the edge in containers.

Production-ready

Access the same robust technology that powers speech recognition across Microsoft products.

Accurately transcribe speech from various sources

Convert audio to text from a range of sources, including  microphones ,  audio files , and  blob storage . Use speaker diarisation to determine who said what and when. Get readable transcripts with automatic formatting and punctuation.

Customize speech models to your needs

Tailor your speech models to understand organization- and industry-specific terminology. Overcome speech recognition barriers such as background noise, accents, or unique vocabulary.  Customize your models  by uploading audio data and transcripts. Automatically  generate custom models using Office 365 data  to optimize speech recognition accuracy for your organization.

Deploy anywhere

Run Speech to Text wherever your data resides. Build speech applications that are optimized for robust cloud capabilities and on-premises using  containers .

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Comprehensive privacy and security

AI Speech, part of Azure AI Services, is  certified  by SOC, FedRAMP, PCI DSS, HIPAA, HITECH, and ISO.

View and delete your custom speech data and models at any time. Your data is encrypted while it's in storage.

Your data remains yours. Your audio input and transcription data aren't logged during audio processing.

Backed by Azure infrastructure, AI Speech offers enterprise-grade security, availability, compliance, and manageability.

Comprehensive security and compliance, built in

Microsoft invests more than $1 billion annually on cybersecurity research and development.

We employ more than 3,500 security experts who are dedicated to data security and privacy.

Azure has more certifications than any other cloud provider. View the comprehensive list .

Flexible pricing gives you the control you need

With Speech to Text, pay as you go based on the number of hours of audio you transcribe, with no upfront costs.

Get started with an Azure free account

After your credit, move to  pay as you go  to keep building with the same free services. Pay only if you use more than your free monthly amounts.

Documentation and resources

Get started.

Browse the  documentation

Create an AI Speech service with the  Microsoft Learn course

Explore code samples

Check out our  sample code

See customization resources

Explore and customize your voice-to-text solution with  Speech Studio . No code required.

Frequently asked questions about Speech to Text

What is speech to text.

It is a feature within the Speech service that accurately and quickly transcribes audio to text.

What are Azure AI Services?

AI Services  are a collection of customizable, prebuilt AI models that can be used to add AI to applications. There are a variety of domains, including Speech, Decision, Language, and Vision. Speech to Text is one feature within the Speech service. Other Speech related features include  Text to Speech ,  Speech Translation , and  Speaker Recognition . An example of a Decision service is  Personalizer , which allows you to deliver personalized, relevant experiences. Examples of AI Languages include  Language Understanding ,  Text Analytics  for natural language processing,  QnA Maker  for FAQ experiences, and  Translator  for language translation.

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What is Speech to Text?

Speech-to-text, also known as speech recognition, allows for the real-time transcription of audio streams into text. This is also known as computer speech recognition. Simply put, speech to text listens to verbal audio recordings and creates a written verbatim script. When users speak clearly, script accuracy rates exceed 95%. The transcribed text can be utilized by applications, tools, and devices as command input. There are two main types of speech to text: speaker dependent which is mostly used for dictation software and speaker independent which is used for phone applications. 

How is Speech to Text Used? 

Speech to text is used to help professionals in various fields in need of high quality transcriptions. Advances in technology have made speech to text transcription faster, cheaper, and more convenient than manual transcription. Speech to text is also important for equal access and digital accessibility. 

Below are some real-life examples of speech-to-text:

1. Voice Typing

Apps allow users to dictate long texts. They can be used for texting, emails, and documents.

2. Voice Commanding

Users can trigger specific actions by voice. Examples of command and control are entering query text by voice and selecting menu items by voice.

3. Voice translation

Customers can use Speech-to-Text technology to communicate with users who speak different languages.

Speech to Text vs Transcription 

Transcription is a human made version of speech to text. Instead of an application or algorithm listening to an audio and creating a verbatim script, a person will listen to the audio and type what is heard. Transcription is a much longer and more costly process than speech to text. Though speech to text still requires human input to run the system and ensure correctness of each script. With modern technological updates, speech to text most often outperforms transcription. Human transcription does offer the benefit of understanding accents, emotion and languages. Typically, human transcription performs best in terms of accuracy, while speech to text outperforms in speed and efficiency. 

Advantages of Using Speech to Text 

Speech to text allows users to improve several different daily processes, and prices vary based on the program used. It is cost efficient when compared to human transcription services. Some services are free but may not yield the highest level of quality. It can also offer a convenient and user-friendly alternative to typing, whether used for dictation, word processing, or navigating the web. Speech to text has allowed users with disabilities to type on and operate computers. As speech to text continues to develop it has been specialized to transcribe audio for industries with advanced technical language. These industries include the medical, construction, and technology fields. 

How Does Speech to Text Work?

Speech to text software analyzes vibrations created from an individual when they speak. Vibrations and frequency are broken down and analyzed to create phonemes. Phonemes are units of sound that differentiate between different words. These phonemes are then run through mathematical equations to create sentences. These sentences reflect the original audio spoken by the user. This text can be consumed, displayed, and acted upon by applications, tools, and devices as command input. Different speech to text softwares produce results at varying speeds and accuracy levels.

• Text To Speech

Text to Speech vs Speech to Text: What is the Difference?

Learn all about the differences between text to speech and speech to text technology.

Picture this: You're driving to work, and your smartphone reads out your unread emails using text-to-speech software (TTS). Better yet, you send off your responses without even needing to touch your phone or look away from the road—all thanks to Speech to Text (STT) software. 

These technologies aren't just fun, futuristic concepts. They're rapidly becoming integral parts of our daily lives, simplifying daily tasks and enhancing accessibility. 

Let’s dive into the world of artificial intelligence-powered TTS and STT, exploring what they are, their differences, how they work, what to look for in TTS and STT providers, and the various ways they're being applied across industries. 

The Differences Between TTS and Text From Speech

There are several key differences between TTS and text-from-speech technology. These are as follows.

Functionality

TTS (TTS) converts written text into spoken words, while Speech to Text (STT) does the opposite, transcribing spoken words into text. TTS is used to make written content audible, acting as a voice assistant for those with visual impairments or learning disabilities. STT, on the other hand, captures spoken language and turns it into a written transcript, beneficial for dictation and voice commands.

Usage Context

TTS is commonly integrated into e-readers, public announcement systems, and virtual assistants to provide auditory output. STT finds its use in transcription services, voice-controlled applications, and real-time captioning for the hearing impaired. The usage context for TTS is primarily output-driven, focusing on delivering information audibly. In contrast, STT is input-centric, focusing on capturing and processing spoken language.

Technological Approach

TTS technology involves text analysis, language processing, and speech synthesis. It must accurately convey the nuances of spoken language, including intonation and rhythm. STT requires advanced voice recognition capabilities to accurately transcribe different accents, dialects, and speech patterns, often in real-time.

What is TTS (TTS)?

TTS (TTS) is a technology that converts written text into spoken words. At its core, TTS enables computers to read aloud, transforming any text into a synthetic voice. This technology finds extensive use in applications ranging from virtual assistants to accessibility tools for those with reading difficulties.

A notable example of advanced TTS technology is ElevenLabs' TTS capabilities. ElevenLabs' TTS stands out for its ability to produce exceptionally natural and human-like voice outputs. It achieves this by leveraging sophisticated AI algorithms that not only mimic the sound of human speech but also understand and reproduce the nuances and inflections that characterize natural speech patterns. 

This level of realism makes ElevenLabs' TTS ideal for creating engaging audio content for various media, enhancing user interfaces with voice feedback, and offering an accessible reading alternative for visually impaired users.

What is Text from Speech (Speech to Text, STT)?

Text from Speech, also known as Speech to Text (STT), is the process of converting spoken language into written text. This speech recognition technology is pivotal in creating transcriptions from audio recordings, enabling voice commands, and facilitating real-time captioning for accessibility.

Several major providers have made significant advancements in STT technology. For instance, Otter.ai revolutionizes automated transcription with its AI-powered tool, efficiently converting audio and video into text. It offers features like AI-powered summaries, searchable transcripts, and a user-friendly interface, making it ideal for capturing meetings, lectures, and interviews in written form.

Microsoft Azure Speech to Text, another leading provider, excels in high-quality transcriptions, supporting more than 100 languages. Its customizable models and flexible deployment options cater to a wide range of professional needs, from creating searchable databases of audio files to enhancing app interactions with voice recognition.

Apple's Siri integrates STT into its ecosystem, offering versatile speech-to-text functionality across various devices. Siri's voice-to-text feature is particularly useful for hands-free operations, such as sending messages or composing emails, making everyday tasks more efficient for Apple users.

How Does TTS Work?

TTS (TTS) technology transforms written text into audible speech, a process that involves several intricate steps.

Initially, the TTS system dissects the text, segmenting it into phonemes - these are the smallest sound units in any language. This segmentation is vital for the system's ability to accurately pronounce various words.

Following this phonemic segmentation, the system proceeds to convert these sounds into digital speech. Here, artificial intelligence (AI) plays a crucial role. Leveraging AI algorithms trained on extensive spoken language datasets, the system can produce speech that echoes human-like tones and rhythms. This generated speech is then aligned with the identified phonemes, culminating in a natural-sounding output.

Thanks to advancements in AI and machine learning, modern TTS technologies have evolved remarkably. They are now capable of understanding contextual nuances, accommodating multiple languages, and somewhat emulating emotional inflections. These enhancements have significantly humanized the speech output, leading to more natural and engaging interactions with digital devices.

What Are the Best TTS Providers?

The best TTS software solutions are ElevenLabs , Murf, and PlayHT. Here’s a brief rundown of their main features, pros, cons, and rating out of 5. 

How Does Speech-to-Text Work?

Speech-to-Text (STT) technology transforms spoken language into written text through a complex, multi-step process.

Firstly, it starts with capturing spoken words, typically through a microphone. This audio input is then converted into a digital format that the system can process. The core of STT lies in its ability to analyze this digital audio. It uses sophisticated algorithms to break down the speech into smaller, recognizable segments.

These segments are phonemes, the smallest units of sound in speech. The STT system matches these phonemes against a pre-defined linguistic model to identify words and phrases. This step is crucial for understanding different accents, dialects, and variations in speech.

Next, the system applies natural language processing (NLP) techniques. NLP helps in understanding the context and syntax of the spoken language, enabling more accurate transcription. It also allows the system to handle complex sentence structures and industry-specific jargon.

Advanced STT systems employ machine learning and deep learning algorithms, which improve with more data and usage. These technologies enable the system to learn from new speech patterns, accents, and even languages over time, enhancing its accuracy and efficiency.

In summary, STT technology involves audio capture, phonemic analysis, linguistic modeling, and NLP, all underpinned by machine learning, to effectively convert speech into text.

What Are the Best Speech-to-Text Providers?

The best speech-to-text providers are Otter, Microsoft Azure, and Siri. Here’s a brief rundown of their main features, pros, cons, and rating out of 5. 

TTS and STT: Accuracy and Challenges

TTS and Speech to Text technologies strive for human-like precision. Their accuracy is constantly improving—but that’s not to say it’s perfect. Here’s what you can expect in terms of accuracy and challenges from both these technologies.

TTS (TTS) Accuracy and Challenges

AI voice TTS technology has significantly evolved, yet it faces challenges. The foremost is achieving natural-sounding human voices. While modern TTS systems can produce clear and understandable audio output, infusing human-like inflections and emotions remains a hurdle. Additionally, TTS struggles with context interpretation, sometimes mispronouncing words based on their context. Another challenge is the customization of voices to suit diverse needs, such as different accents and speech patterns, which is essential for global accessibility.

Text from Speech/Speech to Text (STT) Accuracy and Challenges

STT technology has made strides in accuracy, particularly with the advent of deep learning. However, it encounters difficulties in noisy environments where background sounds can interfere with voice recognition. Accurately capturing and transcribing diverse accents and dialects also poses a significant challenge. Furthermore, STT systems often struggle with homophones (words that sound the same but have different meanings) and understanding complex syntax or slang, impacting their overall effectiveness in real-world applications.

Applications in Various Industries

TTS and Speech to Text technologies have found innovative use cases across a wide variety of industries, transforming how we interact with information and enhancing accessibility.

TTS Applications in Industries

TTS technology finds its application in various sectors. In education, it assists in creating accessible learning materials for students with reading difficulties or visual impairments. For example, like tuning textbooks into audiobooks.

In the automotive industry, TTS powers voice responses in navigation systems. The customer service sector utilizes TTS for automated responses in call centers, enhancing efficiency. Additionally, TTS is instrumental in the entertainment industry, notably in gaming and virtual assistants, where it provides interactive user experiences.

STT Applications in Industries

STT technology has diverse applications across multiple industries. In healthcare, it aids in transcribing doctor-patient conversations and dictating clinical documentation, thereby improving efficiency. In the legal field, STT is used for transcribing court proceedings and legal documentation. The technology also plays a pivotal role in media, aiding in real-time captioning of broadcasts for the hearing impaired. In the corporate world, STT facilitates efficient meeting transcriptions, enhancing record-keeping and accessibility of information.

Final Thoughts

TTS (TTS) and Speech to Text (STT) technologies, while seemingly similar, serve distinct functions. TTS transforms written text into spoken words, bringing written content to life with human-like voices. In contrast, STT does the opposite, converting spoken words into written text, capturing the nuances of spoken language in a textual format. 

Both technologies leverage advanced AI, but they cater to different needs: TTS for auditory consumption of written material, and STT for creating written records of spoken content.

For those interested in experiencing state-of-the-art TTS technology, check out ElevenLabs’ platform . You won’t be disappointed. 

Try ElevenLabs today

The best dictation software in 2024

These speech-to-text apps will save you time without sacrificing accuracy..

The early days of dictation software were like your friend that mishears lyrics: lots of enthusiasm but little accuracy. Now, AI is out of Pandora's box, both in the news and in the apps we use, and dictation apps are getting better and better because of it. It's still not 100% perfect, but you'll definitely feel more in control when using your voice to type.

I took to the internet to find the best speech-to-text software out there right now, and after monologuing at length in front of dozens of dictation apps, these are my picks for the best.

The best dictation software

Windows 11 Speech Recognition for free dictation software on Windows

Dragon by Nuance for a customizable dictation app

Google Docs voice typing for dictating in Google Docs

Gboard for a free mobile dictation app

Otter for collaboration

What is dictation software?

When searching for dictation software online, you'll come across a wide range of options. The ones I'm focusing on here are apps or services that you can quickly open, start talking, and see the results on your screen in (near) real-time. This is great for taking quick notes , writing emails without typing, or talking out an entire novel while you walk in your favorite park—because why not.

Beyond these productivity uses, people with disabilities or with carpal tunnel syndrome can use this software to type more easily. It makes technology more accessible to everyone .

If this isn't what you're looking for, here's what else is out there:

AI assistants, such as Apple's Siri, Amazon's Alexa, and Microsoft's Cortana, can help you interact with each of these ecosystems to send texts, buy products, or schedule events on your calendar.

AI meeting assistants will join your meetings and transcribe everything, generating meeting notes to share with your team.

AI transcription platforms can process your video and audio files into neat text.

Transcription services that use a combination of dictation software, AI, and human proofreaders can achieve above 99% accuracy.

There are also advanced platforms for enterprise, like Amazon Transcribe and Microsoft Azure's speech-to-text services.

What makes a great dictation app?

How we evaluate and test apps.

Our best apps roundups are written by humans who've spent much of their careers using, testing, and writing about software. Unless explicitly stated, we spend dozens of hours researching and testing apps, using each app as it's intended to be used and evaluating it against the criteria we set for the category. We're never paid for placement in our articles from any app or for links to any site—we value the trust readers put in us to offer authentic evaluations of the categories and apps we review. For more details on our process, read the full rundown of how we select apps to feature on the Zapier blog .

Dictation software comes in different shapes and sizes. Some are integrated in products you already use. Others are separate apps that offer a range of extra features. While each can vary in look and feel, here's what I looked for to find the best:

High accuracy. Staying true to what you're saying is the most important feature here. The lowest score on this list is at 92% accuracy.

Ease of use. This isn't a high hurdle, as most options are basic enough that anyone can figure them out in seconds.

Availability of voice commands. These let you add "instructions" while you're dictating, such as adding punctuation, starting a new paragraph, or more complex commands like capitalizing all the words in a sentence.

Availability of the languages supported. Most of the picks here support a decent (or impressive) number of languages.

Versatility. I paid attention to how well the software could adapt to different circumstances, apps, and systems.

I tested these apps by reading a 200-word script containing numbers, compound words, and a few tricky terms. I read the script three times for each app: the accuracy scores are an average of all attempts. Finally, I used the voice commands to delete and format text and to control the app's features where available.

I used my laptop's or smartphone's microphone to test these apps in a quiet room without background noise. For occasional dictation, an equivalent microphone on your own computer or smartphone should do the job well. If you're doing a lot of dictation every day, it's probably worth investing in an external microphone, like the Jabra Evolve .

What about AI?

Before the ChatGPT boom, AI wasn't as hot a keyword, but it already existed. The apps on this list use a combination of technologies that may include AI— machine learning and natural language processing (NLP) in particular. While they could rebrand themselves to keep up with the hype, they may use pipelines or models that aren't as bleeding-edge when compared to what's going on in Hugging Face or under OpenAI Whisper 's hood, for example. 

Also, since this isn't a hot AI software category, these apps may prefer to focus on their core offering and product quality instead, not ride the trendy wave by slapping "AI-powered" on every web page.

Tips for using voice recognition software

Though dictation software is pretty good at recognizing different voices, it's not perfect. Here are some tips to make it work as best as possible.

Speak naturally (with caveats). Dictation apps learn your voice and speech patterns over time. And if you're going to spend any time with them, you want to be comfortable. Speak naturally. If you're not getting 90% accuracy initially, try enunciating more.  

Punctuate. When you dictate, you have to say each period, comma, question mark, and so forth. The software isn't always smart enough to figure it out on its own.

Learn a few commands . Take the time to learn a few simple commands, such as "new line" to enter a line break. There are different commands for composing, editing, and operating your device. Commands may differ from app to app, so learn the ones that apply to the tool you choose.

Know your limits. Especially on mobile devices, some tools have a time limit for how long they can listen—sometimes for as little as 10 seconds. Glance at the screen from time to time to make sure you haven't blown past the mark. 

Practice. It takes time to adjust to voice recognition software, but it gets easier the more you practice. Some of the more sophisticated apps invite you to train by reading passages or doing other short drills. Don't shy away from tutorials, help menus, and on-screen cheat sheets.

The best dictation software at a glance

Best free dictation software for apple devices, apple dictation (ios, ipados, macos).

Look no further than your Mac, iPhone, or iPad for one of the best dictation tools. Apple's built-in dictation feature, powered by Siri (I wouldn't be surprised if the two merged one day), ships as part of Apple's desktop and mobile operating systems. On iOS devices, you use it by pressing the microphone icon on the stock keyboard. On your desktop, you turn it on by going to System Preferences > Keyboard > Dictation , and then use a keyboard shortcut to activate it in your app.

If you want the ability to navigate your Mac with your voice and use dictation, try Voice Control . By default, Voice Control requires the internet to work and has a time limit of about 30 seconds for each smattering of speech. To remove those limits for a Mac, enable Enhanced Dictation, and follow the directions here for your OS (you can also enable it for iPhones and iPads). Enhanced Dictation adds a local file to your device so that you can dictate offline.

You can format and edit your text using simple commands, such as "new paragraph" or "select previous word." Tip: you can view available commands in a small window, like a little cheat sheet, while learning the ropes. Apple also offers a number of advanced commands for things like math, currency, and formatting. 

Apple Dictation price: Included with macOS, iOS, iPadOS, and Apple Watch.

Apple Dictation accuracy: 96%. I tested this on an iPhone SE 3rd Gen using the dictation feature on the keyboard.

Recommendation: For the occasional dictation, I'd recommend the standard Dictation feature available with all Apple systems. But if you need more custom voice features (e.g., medical terms), opt for Voice Control with Enhanced Dictation. You can create and import both custom vocabulary and custom commands and work while offline.

Apple Dictation supported languages: 59 languages and dialects .

While Apple Dictation is available natively on the Apple Watch, if you're serious about recording plenty of voice notes and memos, check out the Just Press Record app. It runs on the same engine and keeps all your recordings synced and organized across your Apple devices.

Best free dictation software for Windows

Windows 11 speech recognition (windows).

Windows 11 Speech Recognition (also known as Voice Typing) is a strong dictation tool, both for writing documents and controlling your Windows PC. Since it's part of your system, you can use it in any app you have installed.

To start, first, check that online speech recognition is on by going to Settings > Time and Language > Speech . To begin dictating, open an app, and on your keyboard, press the Windows logo key + H. A microphone icon and gray box will appear at the top of your screen. Make sure your cursor is in the space where you want to dictate.

When it's ready for your dictation, it will say Listening . You have about 10 seconds to start talking before the microphone turns off. If that happens, just click it again and wait for Listening to pop up. To stop the dictation, click the microphone icon again or say "stop talking."  

As I dictated into a Word document, the gray box reminded me to hang on, we need a moment to catch up . If you're speaking too fast, you'll also notice your transcribed words aren't keeping up. This never posed an issue with accuracy, but it's a nice reminder to keep it slow and steady. 

To activate the computer control features, you'll have to go to Settings > Accessibility > Speech instead. While there, tick on Windows Speech Recognition. This unlocks a range of new voice commands that can fully replace a mouse and keyboard. Your voice becomes the main way of interacting with your system.

While you can use this tool anywhere inside your computer, if you're a Microsoft 365 subscriber, you'll be able to use the dictation features there too. The best app to use it on is, of course, Microsoft Word: it even offers file transcription, so you can upload a WAV or MP3 file and turn it into text. The engine is the same, provided by Microsoft Speech Services.

Windows 11 Speech Recognition price: Included with Windows 11. Also available as part of the Microsoft 365 subscription.

Windows 11 Speech Recognition accuracy: 95%. I tested it in Windows 11 while using Microsoft Word. 

Windows 11 Speech Recognition languages supported : 11 languages and dialects .

Best customizable dictation software

Dragon by nuance (android, ios, macos, windows).

In 1990, Dragon Dictate emerged as the first dictation software. Over three decades later, we have Dragon by Nuance, a leader in the industry and a distant cousin of that first iteration. With a variety of software packages and mobile apps for different use cases (e.g., legal, medical, law enforcement), Dragon can handle specialized industry vocabulary, and it comes with excellent features, such as the ability to transcribe text from an audio file you upload. 

For this test, I used Dragon Anywhere, Nuance's mobile app, as it's the only version—among otherwise expensive packages—available with a free trial. It includes lots of features not found in the others, like Words, which lets you add words that would be difficult to recognize and spell out. For example, in the script, the word "Litmus'" (with the possessive) gave every app trouble. To avoid this, I added it to Words, trained it a few times with my voice, and was then able to transcribe it accurately.

It also provides shortcuts. If you want to shorten your entire address to one word, go to Auto-Text , give it a name ("address"), and type in your address: 1000 Eichhorn St., Davenport, IA 52722, and hit Save . The next time you dictate and say "address," you'll get the entire thing. Press the comment bubble icon to see text commands while you're dictating, or say "What can I say?" and the command menu pops up. 

Once you complete a dictation, you can email, share (e.g., Google Drive, Dropbox), open in Word, or save to Evernote. You can perform these actions manually or by voice command (e.g., "save to Evernote.") Once you name it, it automatically saves in Documents for later review or sharing. 

Accuracy is good and improves with use, showing that you can definitely train your dragon. It's a great choice if you're serious about dictation and plan to use it every day, but may be a bit too much if you're just using it occasionally.

Dragon by Nuance price: $15/month for Dragon Anywhere (iOS and Android); from $200 to $500 for desktop packages

Dragon by Nuance accuracy: 97%. Tested it in the Dragon Anywhere iOS app.

Dragon by Nuance supported languages: 6 languages and dialects in Dragon Anywhere and 8 languages and dialects in Dragon Desktop.  

Best free mobile dictation software

Gboard (android, ios).

Gboard, also known as Google Keyboard, is a free keyboard native to Android phones. It's also available for iOS: go to the App Store, download the Gboard app , and then activate the keyboard in the settings. In addition to typing, it lets you search the web, translate text, or run a quick Google Maps search.

Back to the topic: it has an excellent dictation feature. To start, press the microphone icon on the top-right of the keyboard. An overlay appears on the screen, filling itself with the words you're saying. It's very quick and accurate, which will feel great for fast-talkers but probably intimidating for the more thoughtful among us. If you stop talking for a few seconds, the overlay disappears, and Gboard pastes what it heard into the app you're using. When this happens, tap the microphone icon again to continue talking.

Wherever you can open a keyboard while using your phone, you can have Gboard supporting you there. You can write emails or notes or use any other app with an input field.

The writer who handled the previous update of this list had been using Gboard for seven years, so it had plenty of training data to adapt to his particular enunciation, landing the accuracy at an amazing 98%. I haven't used it much before, so the best I had was 92% overall. It's still a great score. More than that, it's proof of how dictation apps improve the more you use them.

Gboard price : Free

Gboard accuracy: 92%. With training, it can go up to 98%. I tested it using the iOS app while writing a new email.

Gboard supported languages: 916 languages and dialects .

Best dictation software for typing in Google Docs

Google docs voice typing (web on chrome).

Just like Microsoft offers dictation in their Office products, Google does the same for their Workspace suite. The best place to use the voice typing feature is in Google Docs, but you can also dictate speaker notes in Google Slides as a way to prepare for your presentation.

To get started, make sure you're using Chrome and have a Google Docs file open. Go to Tools > Voice typing , and press the microphone icon to start. As you talk, the text will jitter into existence in the document.

You can change the language in the dropdown on top of the microphone icon. If you need help, hover over that icon, and click the ? on the bottom-right. That will show everything from turning on the mic, the voice commands for dictation, and moving around the document.

It's unclear whether Google's voice typing here is connected to the same engine in Gboard. I wasn't able to confirm whether the training data for the mobile keyboard and this tool are connected in any way. Still, the engines feel very similar and turned out the same accuracy at 92%. If you start using it more often, it may adapt to your particular enunciation and be more accurate in the long run.

Google Docs voice typing price : Free

Google Docs voice typing accuracy: 92%. Tested in a new Google Docs file in Chrome.

Google Docs voice typing supported languages: 118 languages and dialects ; voice commands only available in English.

Google Docs integrates with Zapier , which means you can automatically do things like save form entries to Google Docs, create new documents whenever something happens in your other apps, or create project management tasks for each new document.

Best dictation software for collaboration

Otter (web, android, ios).

Most of the time, you're dictating for yourself: your notes, emails, or documents. But there may be situations in which sharing and collaboration is more important. For those moments, Otter is the better option.

It's not as robust in terms of dictation as others on the list, but it compensates with its versatility. It's a meeting assistant, first and foremost, ready to hop on your meetings and transcribe everything it hears. This is great to keep track of what's happening there, making the text available for sharing by generating a link or in the corresponding team workspace.

The reason why it's the best for collaboration is that others can highlight parts of the transcript and leave their comments. It also separates multiple speakers, in case you're recording a conversation, so that's an extra headache-saver if you use dictation software for interviewing people.

When you open the app and click the Record button on the top-right, you can use it as a traditional dictation app. It doesn't support voice commands, but it has decent intuition as to where the commas and periods should go based on the intonation and rhythm of your voice. Once you're done talking, Otter will start processing what you said, extract keywords, and generate action items and notes from the content of the transcription.

If you're going for long recording stretches where you talk about multiple topics, there's an AI chat option, where you can ask Otter questions about the transcript. This is great to summarize the entire talk, extract insights, and get a different angle on everything you said.

Not all meeting assistants offer dictation, so Otter sits here on this fence between software categories, a jack-of-two-trades, quite good at both. If you want something more specialized for meetings, be sure to check out the best AI meeting assistants . But if you want a pure dictation app with plenty of voice commands and great control over the final result, the other options above will serve you better.

Otter price: Free plan available for 300 minutes / month. Pro plan starts at $16.99, adding more collaboration features and monthly minutes.

Otter accuracy: 93% accuracy. I tested it in the web app on my computer.

Otter supported languages: Only American and British English for now.

Is voice dictation for you?

Dictation software isn't for everyone. It will likely take practice learning to "write" out loud because it will feel unnatural. But once you get comfortable with it, you'll be able to write from anywhere on any device without the need for a keyboard. 

And by using any of the apps I listed here, you can feel confident that most of what you dictate will be accurately captured on the screen. 

Related reading:

The best transcription services

Catch typos by making your computer read to you

Why everyone should try the accessibility features on their computer

What is Otter.ai?

The best voice recording apps for iPhone

This article was originally published in April 2016 and has also had contributions from Emily Esposito, Jill Duffy, and Chris Hawkins. The most recent update was in November 2023.

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Miguel Rebelo is a freelance writer based in London, UK. He loves technology, video games, and huge forests. Track him down at mirebelo.com.

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Best speech-to-text app of 2024

Free, paid and online voice recognition apps and services

Best overall

Best for business, best for mobile, best text service, best speech recognition, best virtual assistant, best for cloud, best for azure, best for batch conversion, best free speech to text apps, best mobile speech to text apps.

• How we test

The best speech-to-text apps make it simple and easy to convert speech into text, for both desktop and mobile devices.

1. Best overall 2. Best for business 3. Best for mobile 4. Best text service 5. Best speech recognition 6. Best virtual assistant 7. Best for cloud 8. Best for Azure 9. Best for batch conversion 10. Best free speech to text apps 11. Best mobile speech to text apps 12. FAQs 13. How we test

Speech-to-text used to be regarded as very niche, specifically serving either people with accessibility needs or for  dictation . However, speech-to-text is moving more and more into the mainstream as office work can now routinely be completed more simply and easily by using voce-recognition software, rather than having to type through members, and speaking aloud for text to be recorded is now quite common.

While the best speech to text software used to be specifically only for desktops, the development of mobile devices and the explosion of easily accessible apps means that transcription can now also be carried out on a  smartphone  or  tablet . 

This has made the best voice to text applications increasingly valuable to users in a range of different environments, from education to business. This is not least because the technology has matured to the level where mistakes in transcriptions are relatively rare, with some services rightly boasting a 99.9% success rate from clear audio.

Even still, this applies mainly to ordinary situations and circumstances, and precludes the use of technical terminology such as required in legal or medical professions. Despite this, digital transcription can still service needs such as basic  note-taking  which can still be easily done using a phone app, simplifying the dictation process.

However, different speech-to-text programs have different levels of ability and complexity, with some using advanced machine learning to constantly correct errors flagged up by users so that they are not repeated. Others are downloadable software which is only as good as its latest update.

Here then are the best in speech-to-text recognition programs, which should be more than capable for most situations and circumstances.

We've also featured the best voice recognition software .

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The best paid for speech to text apps of 2024 in full:

Why you can trust TechRadar We spend hours testing every product or service we review, so you can be sure you’re buying the best. Find out more about how we test.

1. Dragon Anywhere

Our expert review:

Reasons to buy

Reasons to avoid.

Dragon Anywhere is the Nuance mobile product for Android and iOS devices, however this is no ‘lite’ app, but rather offers fully-formed dictation capabilities powered via the cloud. 

So essentially you get the same excellent speech recognition as seen on the desktop software – the only meaningful difference we noticed was a very slight delay in our spoken words appearing on the screen (doubtless due to processing in the cloud). However, note that the app was still responsive enough overall.

It also boasts support for boilerplate chunks of text which can be set up and inserted into a document with a simple command, and these, along with custom vocabularies, are synced across the mobile app and desktop Dragon software. Furthermore, you can share documents across devices via Evernote or cloud services (such as Dropbox).

This isn’t as flexible as the desktop application, however, as dictation is limited to within Dragon Anywhere – you can’t dictate directly in another app (although you can copy over text from the Dragon Anywhere dictation pad to a third-party app). The other caveats are the need for an internet connection for the app to work (due to its cloud-powered nature), and the fact that it’s a subscription offering with no one-off purchase option, which might not be to everyone’s tastes.

Even bearing in mind these limitations, though, it’s a definite boon to have fully-fledged, powerful voice recognition of the same sterling quality as the desktop software, nestling on your phone or tablet for when you’re away from the office.

Nuance Communications offers a 7-day free trial to give the app a try before you commit to a subscription. 

Read our full Dragon Anywhere review .

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2. Dragon Professional

Should you be looking for a business-grade dictation application, your best bet is Dragon Professional. Aimed at pro users, the software provides you with the tools to dictate and edit documents, create spreadsheets, and browse the web using your voice.   

According to Nuance, the solution is capable of taking dictation at an equivalent typing speed of 160 words per minute, with a 99% accuracy rate – and that’s out-of-the-box, before any training is done (whereby the app adapts to your voice and words you commonly use).

As well as creating documents using your voice, you can also import custom word lists. There’s also an additional mobile app that lets you transcribe audio files and send them back to your computer.   

This is a powerful, flexible, and hugely useful tool that is especially good for individuals, such as professionals and freelancers, allowing for typing and document management to be done much more flexibly and easily.

Overall, the interface is easy to use, and if you get stuck at all, you can access a series of help tutorials. And while the software can seem expensive, it's just a one-time fee and compares very favorably with paid-for subscription transcription services.

Also note that Nuance are currently offering 12-months' access to Dragon Anywhere at no extra cost with any purchase of Dragon Home or Dragon Professional Individual.

Read our full Dragon Professional review .

Otter is a cloud-based speech to text program especially aimed for mobile use, such as on a laptop or smartphone. The app provides real-time transcription, allowing you to search, edit, play, and organize as required.

Otter is marketed as an app specifically for meetings, interviews, and lectures, to make it easier to take rich notes. However, it is also built to work with collaboration between teams, and different speakers are assigned different speaker IDs to make it easier to understand transcriptions.

There are three different payment plans, with the basic one being free to use and aside from the features mentioned above also includes keyword summaries and a wordcloud to make it easier to find specific topic mentions. You can also organize and share, import audio and video for transcription, and provides 600 minutes of free service.

The Premium plan also includes advanced and bulk export options, the ability to sync audio from Dropbox, additional playback speeds including the ability to skip silent pauses. The Premium plan also allows for up to 6,000 minutes of speech to text.

The Teams plan also adds two-factor authentication, user management and centralized billing, as well as user statistics, voiceprints, and live captioning.

Read our full Otter review .

Verbit aims to offer a smarter speech to text service, using AI for transcription and captioning. The service is specifically targeted at enterprise and educational establishments.

Verbit uses a mix of speech models, using neural networks and algorithms to reduce background noise, focus on terms as well as differentiate between speakers regardless of accent, as well as incorporate contextual events such as news and company information into recordings.

Although Verbit does offer a live version for transcription and captioning, aiming for a high degree of accuracy, other plans offer human editors to ensure transcriptions are fully accurate, and advertise a four hour turnaround time.

Altogether, while Verbit does offer a direct speech to text service, it’s possibly better thought of as a transcription service, but the focus on enterprise and education, as well as team use, means it earns a place here as an option to consider.

Read our full Verbit review .

5. Speechmatics

Speechmatics offers a machine learning solution to converting speech to text, with its automatic speech recognition solution available to use on existing audio and video files as well as for live use.

Unlike some automated transcription software which can struggle with accents or charge more for them, Speechmatics advertises itself as being able to support all major British accents, regardless of nationality. That way it aims to cope with not just different American and British English accents, but also South African and Jamaican accents.

Speechmatics offers a wider number of speech to text transcription uses than many other providers. Examples include taking call center phone recordings and converting them into searchable text or Word documents. The software also works with video and other media for captioning as well as using keyword triggers for management.

Overall, Speechmatics aims to offer a more flexible and comprehensive speech to text service than a lot of other providers, and the use of automation should keep them price competitive.

Read our full Speechmatics review .

6. Braina Pro

Braina Pro is speech recognition software which is built not just for dictation, but also as an all-round digital assistant to help you achieve various tasks on your PC. It supports dictation to third-party software in not just English but almost 90 different languages, with impressive voice recognition chops.

Beyond that, it’s a virtual assistant that can be instructed to set alarms, search your PC for a file, or search the internet, play an MP3 file, read an ebook aloud, plus you can implement various custom commands.

The Windows program also has a companion Android app which can remotely control your PC, and use the local Wi-Fi network to deliver commands to your computer, so you can spark up a music playlist, for example, wherever you happen to be in the house. Nifty.

There’s a free version of Braina which comes with limited functionality, but includes all the basic PC commands, along with a 7-day trial of the speech recognition which allows you to test out its powers for yourself before you commit to a subscription. Yes, this is another subscription-only product with no option to purchase for a one-off fee. Also note that you need to be online and have Google ’s Chrome browser installed for speech recognition functionality to work.

Read our full Braina Pro review .

7. Amazon Transcribe

Amazon Transcribe is as big cloud-based automatic speech recognition platform developed specifically to convert audio to text for apps. It especially aims to provide a more accurate and comprehensive service than traditional providers, such as being able to cope with low-fi and noisy recordings, such as you might get in a contact center .

Amazon Transcribe uses a deep learning process that automatically adds punctuation and formatting, as well as process with a secure livestream or otherwise transcribe speech to text with batch processing.

As well as offering time stamping for individual words for easy search, it can also identify different speaks and different channels and annotate documents accordingly to account for this.

There are also some nice features for editing and managing transcribed texts, such as vocabulary filtering and replacement words which can be used to keep product names consistent and therefore any following transcription easier to analyze.

Overall, Amazon Transcribe is one of the most powerful platforms out there, though it’s aimed more for the business and enterprise user rather than the individual.

8. Microsoft Azure Speech to Text

Microsoft 's Azure cloud service offers advanced speech recognition as part of the platform's speech services to deliver the Microsoft Azure Speech to Text functionality. 

This feature allows you to simply and easily create text from a variety of audio sources. There are also customization options available to work better with different speech patterns, registers, and even background sounds. You can also modify settings to handle different specialist vocabularies, such as product names, technical information, and place names.

The Microsoft's Azure Speech to Text feature is powered by deep neural network models and allows for real-time audio transcription that can be set up to handle multiple speakers.

As part of the Azure cloud service, you can run Azure Speech to Text in the cloud, on premises, or in edge computing. In terms of pricing, you can run the feature in a free container with a single concurrent request for up to 5 hours of free audio per month.

Read our full Microsoft Azure Speech to Text review .

9. IBM Watson Speech to Text

IBM's Watson Speech to Text works is the third cloud-native solution on this list, with the feature being powered by AI and machine learning as part of IBM's cloud services.

While there is the option to transcribe speech to text in real-time, there is also the option to batch convert audio files and process them through a range of language, audio frequency, and other output options.

You can also tag transcriptions with speaker labels, smart formatting, and timestamps, as well as apply global editing for technical words or phrases, acronyms, and for number use.

As with other cloud services Watson Speech to Text allows for easy deployment both in the cloud and on-premises behind your own firewall to ensure security is maintained.

Read our full Watson Speech to Text review .

1. Google Gboard

If you already have an Android mobile device, then if it's not already installed then download Google Keyboard from the Google Play store and you'll have an instant text-to-speech app. Although it's primarily designed as a keyboard for physical input, it also has a speech input option which is directly available. And because all the power of Google's hardware is behind it, it's a powerful and responsive tool.

If that's not enough then there are additional features. Aside from physical input ones such as swiping, you can also trigger images in your text using voice commands. Additionally, it can also work with Google Translate, and is advertised as providing support for over 60 languages.

Even though Google Keyboard isn't a dedicated transcription tool, as there are no shortcut commands or text editing directly integrated, it does everything you need from a basic transcription tool. And as it's a keyboard, it means should be able to work with any software you can run on your Android smartphone, so you can text edit, save, and export using that. Even better, it's free and there are no adverts to get in the way of you using it.

2. Just Press Record

If you want a dedicated dictation app, it’s worth checking out Just Press Record. It’s a mobile audio recorder that comes with features such as one tap recording, transcription and iCloud syncing across devices. The great thing is that it’s aimed at pretty much anyone and is extremely easy to use. 

When it comes to recording notes, all you have to do is press one button, and you get unlimited recording time. However, the really great thing about this app is that it also offers a powerful transcription service. 

Through it, you can quickly and easily turn speech into searchable text. Once you’ve transcribed a file, you can then edit it from within the app. There’s support for more than 30 languages as well, making it the perfect app if you’re working abroad or with an international team. Another nice feature is punctuation command recognition, ensuring that your transcriptions are free from typos.   

This app is underpinned by cloud technology, meaning you can access notes from any device (which is online). You’re able to share audio and text files to other iOS apps too, and when it comes to organizing them, you can view recordings in a comprehensive file. 

3. Speechnotes

Speechnotes is yet another easy to use dictation app. A useful touch here is that you don’t need to create an account or anything like that; you just open up the app and press on the microphone icon, and you’re off.   

The app is powered by Google voice recognition tech. When you’re recording a note, you can easily dictate punctuation marks through voice commands, or by using the built-in punctuation keyboard. 

To make things even easier, you can quickly add names, signatures, greetings and other frequently used text by using a set of custom keys on the built-in keyboard. There’s automatic capitalization as well, and every change made to a note is saved to the cloud.

When it comes to customizing notes, you can access a plethora of fonts and text sizes. The app is free to download from the Google Play Store , but you can make in-app purchases to access premium features (there's also a browser version for Chrome).   

Read our full Speechnotes review .

4. Transcribe

Marketed as a personal assistant for turning videos and voice memos into text files, Transcribe is a popular dictation app that’s powered by AI. It lets you make high quality transcriptions by just hitting a button.   

The app can transcribe any video or voice memo automatically, while supporting over 80 languages from across the world. While you can easily create notes with Transcribe, you can also import files from services such as Dropbox.

Once you’ve transcribed a file, you can export the raw text to a word processor to edit. The app is free to download, but you’ll have to make an in-app purchase if you want to make the most of these features in the long-term. There is a trial available, but it’s basically just 15 minutes of free transcription time. Transcribe is only available on iOS, though.   

5. Windows Speech Recognition

If you don’t want to pay for speech recognition software, and you’re running Microsoft’s latest desktop OS, then you might be pleased to hear that speech-to-text is built into Windows.

Windows Speech Recognition, as it’s imaginatively named – and note that this is something different to Cortana, which offers basic commands and assistant capabilities – lets you not only execute commands via voice control, but also offers the ability to dictate into documents.

The sort of accuracy you get isn’t comparable with that offered by the likes of Dragon, but then again, you’re paying nothing to use it. It’s also possible to improve the accuracy by training the system by reading text, and giving it access to your documents to better learn your vocabulary. It’s definitely worth indulging in some training, particularly if you intend to use the voice recognition feature a fair bit.

The company has been busy boasting about its advances in terms of voice recognition powered by deep neural networks, especially since windows 10 and now for Windows 11 , and Microsoft is certainly priming us to expect impressive things in the future. The likely end-goal aim is for Cortana to do everything eventually, from voice commands to taking dictation.

Turn on Windows Speech Recognition by heading to the Control Panel (search for it, or right click the Start button and select it), then click on Ease of Access, and you will see the option to ‘start speech recognition’ (you’ll also spot the option to set up a microphone here, if you haven’t already done that).

Aside from what has already been covered above, there are an increasing number of apps available across all mobile devices for working with speech to text, not least because Google's speech recognition technology is available for use. 

iTranslate Translator  is a speech-to-text app for iOS with a difference, in that it focuses on translating voice languages. Not only does it aim to translate different languages you hear into text for your own language, it also works to translate images such as photos you might take of signs in a foreign country and get a translation for them. In that way, iTranslate is a very different app, that takes the idea of speech-to-text in a novel direction, and by all accounts, does it well. 

ListNote Speech-to-Text Notes  is another speech-to-text app that uses Google's speech recognition software, but this time does a more comprehensive job of integrating it with a note-taking program than many other apps. The text notes you record are searchable, and you can import/export with other text applications. Additionally there is a password protection option, which encrypts notes after the first 20 characters so that the beginning of the notes are searchable by you. There's also an organizer feature for your notes, using category or assigned color. The app is free on Android, but includes ads.

Voice Notes  is a simple app that aims to convert speech to text for making notes. This is refreshing, as it mixes Google's speech recognition technology with a simple note-taking app, so there are more features to play with here. You can categorize notes, set reminders, and import/export text accordingly.

SpeechTexter  is another speech-to-text app that aims to do more than just record your voice to a text file. This app is built specifically to work with social media, so that rather than sending messages, emails, Tweets, and similar, you can record your voice directly to the social media sites and send. There are also a number of language packs you can download for offline working if you want to use more than just English, which is handy.

Also consider reading these related software and app guides:

• Best text-to-speech software
• Best transcription services
• Best Bluetooth headsets

Speech-to-text app FAQs

Which speech-to-text app is best for you.

When deciding which speech-to-text app to use, first consider what your actual needs are, as free and budget  options may only provide basic features, so if you need to use advanced tools you may find a paid-for platform is better suited to you. Additionally, higher-end software can usually cater for every need, so do ensure you have a good idea of which features you think you may require from your speech-to-text app.

How we tested the best speech-to-text apps

To test for the best speech-to-text apps we first set up an account with the relevant platform, then we tested the service to see how the software could be used for different purposes and in different situations. The aim was to push each speech-to-text platform to see how useful its basic tools were and also how easy it was to get to grips with any more advanced tools.

Read more on how we test, rate, and review products on TechRadar .

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Brian has over 30 years publishing experience as a writer and editor across a range of computing, technology, and marketing titles. He has been interviewed multiple times for the BBC and been a speaker at international conferences. His specialty on techradar is Software as a Service (SaaS) applications, covering everything from office suites to IT service tools. He is also a science fiction and fantasy author, published as Brian G Turner.

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Speech to Text - Voice Typing & Transcription

Take notes with your voice for free, or automatically transcribe audio & video recordings. secure, accurate & blazing fast..

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Dictate Notes

Start taking notes, on our online voice-enabled notepad right away, for free.

Transcribe Recordings

Automatically transcribe audios & videos - upload files from your device or link to an online resource (Drive, YouTube, TikTok and more).

Speechnotes is a reliable and secure web-based speech-to-text tool that enables you to quickly and accurately transcribe your audio and video recordings, as well as dictate your notes instead of typing, saving you time and effort. With features like voice commands for punctuation and formatting, automatic capitalization, and easy import/export options, Speechnotes provides an efficient and user-friendly dictation and transcription experience. Proudly serving millions of users since 2015, Speechnotes is the go-to tool for anyone who needs fast, accurate & private transcription. Our Portfolio of Complementary Speech-To-Text Tools Includes:

Voice typing - Chrome extension

Dictate instead of typing on any form & text-box across the web. Including on Gmail, and more.

Transcription API & webhooks

Speechnotes' API enables you to send us files via standard POST requests, and get the transcription results sent directly to your server.

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Combine the power of automatic transcriptions with Zapier's automatic processes. Serverless & codeless automation! Connect with your CRM, phone calls, Docs, email & more.

Android Speechnotes app

Speechnotes' notepad for Android, for notes taking on your mobile, battle tested with more than 5Million downloads. Rated 4.3+ ⭐

iOS TextHear app

TextHear for iOS, works great on iPhones, iPads & Macs. Designed specifically to help people with hearing impairment participate in conversations. Please note, this is a sister app - so it has its own pricing plan.

Audio & video converting tools

Tools developed for fast - batch conversions of audio files from one type to another and extracting audio only from videos for minimizing uploads.

Our Sister Apps for Text-To-Speech & Live Captioning

Complementary to Speechnotes

Reads out loud texts, files & web pages

Reads out loud texts, PDFs, e-books & websites for free

Speechlogger

Live Captioning & Translation

Live captions & translations for online meetings, webinars, and conferences.

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Dictation Notepad

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Speech to Text online notepad. Professional, accurate & free speech recognizing text editor. Distraction-free, fast, easy to use web app for dictation & typing.

Speechnotes is a powerful speech-enabled online notepad, designed to empower your ideas by implementing a clean & efficient design, so you can focus on your thoughts. We strive to provide the best online dictation tool by engaging cutting-edge speech-recognition technology for the most accurate results technology can achieve today, together with incorporating built-in tools (automatic or manual) to increase users' efficiency, productivity and comfort. Works entirely online in your Chrome browser. No download, no install and even no registration needed, so you can start working right away.

Speechnotes is especially designed to provide you a distraction-free environment. Every note, starts with a new clear white paper, so to stimulate your mind with a clean fresh start. All other elements but the text itself are out of sight by fading out, so you can concentrate on the most important part - your own creativity. In addition to that, speaking instead of typing, enables you to think and speak it out fluently, uninterrupted, which again encourages creative, clear thinking. Fonts and colors all over the app were designed to be sharp and have excellent legibility characteristics.

Example use cases

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Fast turnaround - results within minutes. Includes timestamps, auto punctuation and subtitles at unbeatable price. Protects your privacy: no human in the loop, and (unlike many other vendors) we do NOT keep your audio. Pay per use, no recurring payments. Upload your files or transcribe directly from Google Drive, YouTube or any other online source. Simple. No download or install. Just send us the file and get the results in minutes.

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Key Advantages

Speechnotes is powered by the leading most accurate speech recognition AI engines by Google & Microsoft. We always check - and make sure we still use the best. Accuracy in English is very good and can easily reach 95% accuracy for good quality dictation or recording.

Lightweight & fast

Both Speechnotes dictation & transcription are lightweight-online no install, work out of the box anywhere you are. Dictation works in real time. Transcription will get you results in a matter of minutes.

Super Private & Secure!

Super private - no human handles, sees or listens to your recordings! In addition, we take great measures to protect your privacy. For example, for transcribing your recordings - we pay Google's speech to text engines extra - just so they do not keep your audio for their own research purposes.

Health advantages

Typing may result in different types of Computer Related Repetitive Strain Injuries (RSI). Voice typing is one of the main recommended ways to minimize these risks, as it enables you to sit back comfortably, freeing your arms, hands, shoulders and back altogether.

Saves you time

Need to transcribe a recording? If it's an hour long, transcribing it yourself will take you about 6! hours of work. If you send it to a transcriber - you will get it back in days! Upload it to Speechnotes - it will take you less than a minute, and you will get the results in about 20 minutes to your email.

Saves you money

Speechnotes dictation notepad is completely free - with ads - or a small fee to get it ad-free. Speechnotes transcription is only $0.1/minute, which is X10 times cheaper than a human transcriber! We offer the best deal on the market - whether it's the free dictation notepad ot the pay-as-you-go transcription service.

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Privacy policy.

We at Speechnotes, Speechlogger, TextHear, Speechkeys value your privacy, and that's why we do not store anything you say or type or in fact any other data about you - unless it is solely needed for the purpose of your operation. We don't share it with 3rd parties, other than Google / Microsoft for the speech-to-text engine.

Privacy - how are the recordings and results handled?

- transcription service.

Our transcription service is probably the most private and secure transcription service available.

• HIPAA compliant.
• No human in the loop. No passing your recording between PCs, emails, employees, etc.
• Secure encrypted communications (https) with and between our servers.
• Recordings are automatically deleted from our servers as soon as the transcription is done.
• Our contract with Google / Microsoft (our speech engines providers) prohibits them from keeping any audio or results.
• Transcription results are securely kept on our secure database. Only you have access to them - only if you sign in (or provide your secret credentials through the API)
• You may choose to delete the transcription results - once you do - no copy remains on our servers.

- Dictation notepad & extension

For dictation, the recording & recognition - is delegated to and done by the browser (Chrome / Edge) or operating system (Android). So, we never even have access to the recorded audio, and Edge's / Chrome's / Android's (depending the one you use) privacy policy apply here.

The results of the dictation are saved locally on your machine - via the browser's / app's local storage. It never gets to our servers. So, as long as your device is private - your notes are private.

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The whole payments process is delegated to PayPal / Stripe / Google Pay / Play Store / App Store and secured by these providers. We never receive any of your credit card information.

More generic notes regarding our site, cookies, analytics, ads, etc.

• We may use Google Analytics on our site - which is a generic tool to track usage statistics.
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Electrical Engineering and Systems Science > Audio and Speech Processing

Title: voicecraft: zero-shot speech editing and text-to-speech in the wild.

Abstract: We introduce VoiceCraft, a token infilling neural codec language model, that achieves state-of-the-art performance on both speech editing and zero-shot text-to-speech (TTS) on audiobooks, internet videos, and podcasts. VoiceCraft employs a Transformer decoder architecture and introduces a token rearrangement procedure that combines causal masking and delayed stacking to enable generation within an existing sequence. On speech editing tasks, VoiceCraft produces edited speech that is nearly indistinguishable from unedited recordings in terms of naturalness, as evaluated by humans; for zero-shot TTS, our model outperforms prior SotA models including VALLE and the popular commercial model XTTS-v2. Crucially, the models are evaluated on challenging and realistic datasets, that consist of diverse accents, speaking styles, recording conditions, and background noise and music, and our model performs consistently well compared to other models and real recordings. In particular, for speech editing evaluation, we introduce a high quality, challenging, and realistic dataset named RealEdit. We encourage readers to listen to the demos at this https URL .

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Musk tried to ‘punish’ critics, judge rules, in tossing a lawsuit

In a win for hate-speech researchers, a federal judge in california dismisses x’s lawsuit under the state’s anti-slapp law.

A federal judge in California on Monday threw out the entirety of a lawsuit by Elon Musk’s X against the nonprofit Center for Countering Digital Hate (CCDH), ruling that the lawsuit was an attempt to silence X’s critics.

“X Corp.’s motivation in bringing this case is evident,” U.S. District Judge Charles R. Breyer wrote in a 52-page ruling . “X Corp. has brought this case in order to punish CCDH for CCDH publications that criticized X Corp. — and perhaps in order to dissuade others who might wish to engage in such criticism.”

X sued the Washington, D.C.-based nonprofit in July 2023 after it published a report alleging that the social network was profiting from hate after Musk reinstated scores of previously suspended accounts of “neo-Nazis, white supremacists, misogynists and spreaders of dangerous conspiracy theories.” X alleged that the group improperly gained access to data about X and that its claims influenced advertisers to spend less money on the site, costing X tens of millions of dollars in lost revenue.

The ruling is a win for research groups that study online platforms and a blow to Musk’s campaign to portray X’s loss of advertisers as a vast conspiracy against him. Under Musk, X has also sued the nonprofit Media Matters for America in federal court in Texas, and it threatened to sue the Anti-Defamation League before reaching a détente with that group.

Musk “certainly doesn’t seem to champion free-speech rights when the speaker is being critical of him,” said David Greene, senior staff attorney and civil liberties director at the digital rights nonprofit Electronic Frontier Foundation.

Breyer dismissed the suit under California’s strict laws against what are known as SLAPPs, or strategic lawsuits against public participation. The judge did not mince words in his finding that the suit lacked merit and appeared to be a blatant attempt to intimidate researchers and critics.

“Sometimes it is unclear what is driving a litigation, and only by reading between the lines of a complaint can one attempt to surmise a plaintiff’s true purpose,” Breyer wrote. “Other times, a complaint is so unabashedly and vociferously about one thing that there can be no mistaking that purpose. This case represents the latter circumstance. This case is about punishing the Defendants for their speech.”

Under California’s anti-SLAPP statute, defendants are entitled to have their legal fees paid by the plaintiffs who filed the frivolous suit.

Imran Ahmed, CCDH’s CEO, cheered Breyer’s ruling in a phone interview Monday, calling it a “complete victory” that should “embolden” public-interest researchers everywhere to continue their work.

“It is quite clear that this was an unconstitutional attempt to shut down the free speech of critics of Elon Musk, by Elon Musk, a self-proclaimed ‘free-speech absolutist,’” Ahmed said. “It’s an enormous relief to the team at CCDH that we now can continue our mission to hold these companies accountable.”

Jonathan Hawk, an attorney representing X in the case, declined to comment. Musk could not be reached for comment, and a request for comment from X was met with an autoreply.

Alejandra Caraballo, a clinical instructor at Harvard Law School’s Cyberlaw Clinic, said the ruling was “probably the best decision that could have come out of this case with a view toward actually protecting free speech.” “We don’t want the wealthy, the powerful and others to silence dissent through litigation they know is frivolous just because they have the resources,” Caraballo said.

While Musk has billed himself as a “free-speech absolutist,” he has on several occasions barred journalists and activists from the site for posting information that he said violated its rules. Caraballo experienced that last week when her X account was banned after she amplified the identity of anonymous neo-Nazi comic artist StoneToss. The platform cracked down on mentions of the user’s supposed identity and changed the terms of service to prohibit naming the person behind an anonymous account. (Caraballo’s account has since been reinstated.)

CCDH was one of several research groups that found a rise in hate speech on the site after Musk bought it in October 2022. As some advertisers paused spending on X, Musk attempted to control the damage , claiming in November 2022 that hate speech had fallen “below our prior norms.”

On Nov. 10, 2022, CCDH published what it called a “fact-check” of those claims . The group said data from an analytics tool for advertisers called Brandwatch showed that the use of some particularly vile slurs had spiked dramatically.

In February 2023, another CCDH report titled “ Toxic Twitter ” found that a group of 10 extremist accounts whose bans were lifted by Musk was generating billions of views with their tweets and likely bringing in millions in ad revenue . The implication was that Musk was profiting from the speech of people such as neo-Nazi Andrew Anglin, self-described “misogynist influencer” Andrew Tate and leading vaccine conspiracy theorists.

X cited both reports, along with a previous report that CCDH published before Musk’s purchase of Twitter, in its lawsuit. The company said the group violated its terms of service, improperly used the Brandwatch advertising tool and violated the Computer Fraud and Abuse Act’s provision against unauthorized access to machines and data.

But while X accused CCDH of harming its reputation, it did not bring a legal claim of defamation, which would have required it to prove that the reports were untrue. CCDH’s lawyers suggested that might be because X didn’t want to open itself to a legal discovery process that would generate evidence about “the truth about the content on its platform.”

Breyer, the judge, took note of that choice, writing in his ruling that X wanted to “have it both ways — to be spared the burdens of pleading a defamation claim, while bemoaning the harm to its reputation, and seeking punishing damages based on reputational harm.”

In a similar case, X sued the liberal media watchdog group Media Matters in Texas in November 2023 after it published a report showing that the site appeared to be running ads alongside blatantly pro-Nazi posts. Multiple businesses, including IBM, Apple and Disney, subsequently suspended their advertising on the platform.

“The court made it clear that Elon Musk is using lawsuits to silence critics and would-be critics,” said Angelo Carusone, president of Media Matters, noting that Musk had “enlisted several Republican state [attorney generals] to initiate harassing investigations against us.”

“Today was a good day for free speech, but there is a long road ahead before it can be marked safe from Musk’s abuse,” Carusone said.

Greene said he hopes the high-profile ruling against Musk will discourage others from trying to use frivolous lawsuits as a tool for intimidation and silencing critics. But he said it’s unlikely the CCDH ruling will have any bearing on the pending lawsuit in Texas against Media Matters because “the claims are different,” noting that Musk sued for defamation in that case.

Texas has become a favored venue for Musk as he has battled lawsuits in other jurisdictions. He moved Tesla’s corporate headquarters from California to Austin in 2021, and he moved the incorporation of SpaceX to Texas from Delaware in February, after a Delaware judge voided his $56 billion pay package for Tesla. The day Musk filed his lawsuit against Media Matters, Texas Attorney General Ken Paxton (R) launched a fraud investigation into the nonprofit, subpoenaing materials related to its reporting.

Joseph Menn contributed to this report.

Trump promotes Lee Greenwood's 'God Bless The USA Bible': What to know about the book and its long journey

• Former president Donald Trump encourages supporters to buy Lee Greenwood's "God Bless The USA Bible," a project inspired by Nashville country musician's hit song.
• Resurgent version of Greenwood's Bible project a modified version from original concept, a change that likely followed 2021 shake-up in publishers.

After years with few updates about Lee Greenwood’s controversial Bible, the project is again resurgent with a recent promotion by former President Donald Trump.

“All Americans need to have a Bible in their home and I have many. It’s my favorite book,” Trump said in a video posted to social media Tuesday, encouraging supporters to purchase the “God Bless The USA Bible.” “Religion is so important and so missing, but it’s going to come back.”

Greenwood — the Nashville area country musician whose hit song “God Bless the USA” inspired the Bible with a similar namesake — has long been allies with Trump and other prominent Republicans, many of whom are featured in promotional material for the “God Bless The USA Bible.” But that reputational clout in conservative circles hasn’t necessarily translated to business success in the past, largely due to a major change in the book’s publishing plan.

Here's what to know about the Bible project’s journey so far and why it’s significant it’s back in the conservative limelight.

An unordinary Bible, a fiery debate

The “God Bless The USA Bible” received heightened attention since the outset due to its overt political features.

The text includes the U.S. Constitution, Bill of Rights, Declaration of Independence, Pledge of Allegiance, and the lyrics to the chorus to Greenwood’s “God Bless The USA.” Critics saw it as a symbol of Christian nationalism, a right-wing movement that believes the U.S. was founded as a Christian nation.

A petition emerged in 2021 calling Greenwood’s Bible “a toxic mix that will exacerbate the challenges to American evangelicalism.” From there, a broader conversation ensued about the standards by which publishers print Bibles.

Gatekeeping in Bible publishing

Greenwood’s early business partner on the project, a Hermitage-based marketing firm called Elite Source Pro, initially reached a manufacturing agreement with the Nashville-based HarperCollins Christian Publishing to print the “God Bless The USA Bible.”  

As part of that agreement, HarperCollins would publish the book but not sell or endorse it. But then HarperCollins reversed course , a major setback for Greenwood’s Bible.

The reversal by HarperCollins followed a decision by Zondervan — a publishing group under HarperCollins Christian Publishing and an official North American licensor for Bibles printed in the New International Version translation — to pass on the project. HarperCollins said the decision was unrelated to the petition or other public denunciations against Greenwood’s Bible.

The full backstory: Lee Greenwood's 'God Bless the USA Bible' finds new printer after HarperCollins Christian passes

A new translation and mystery publisher

The resurgent “God Bless The USA Bible” featured in Trump’s recent ad is an altered version of the original concept, a modification that likely followed the publishing shake-up.

Greenwood’s Bible is now printed in the King James Version, a different translation from the original pitch to HarperCollins.

Perhaps the biggest mystery is the new publisher. That manufacturer is producing a limited quantity of copies, leading to a delayed four-to-six weeks for a copy to ship.  

It’s also unclear which business partners are still involved in the project. Hugh Kirkman, who led Elite Service Pro, the firm that originally partnered with Greenwood for the project, responded to a request for comment by referring media inquiries to Greenwood’s publicist.

The publicist said Elite Source Pro is not a partner on the project and the Bible has always been printed in the King James Version.

"Several years ago, the Bible was going to be printed with the NIV translation, but something happened with the then licensor and the then potential publisher. As a result, this God Bless The USA Bible has always been printed with the King James Version translation," publicist Jeremy Westby said in a statement.

Westby did not have the name of the new licensee who is manufacturing the Bible.

Trump’s plug for the “God Bless The USA Bible” recycled language the former president is using to appeal to a conservative Christian base.

“Our founding fathers did a tremendous thing when they built America on Judeo-Christian values,” Trump said in his video on social media. “Now that foundation is under attack perhaps as never before.”

'Bring back our religion’: Trump vows to support Christians during Nashville speech

Liam Adams covers religion for The Tennessean. Reach him at [email protected] or on social media @liamsadams.

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Judge dismisses Elon Musk's suit against hate speech researchers

Bobby Allyn

Elon Musk, owner of X, sued the Center for Countering Digital Hate after the group published a series of reports detailing an uptick of hate speech on X, the social media platform formerly known as Twitter. Czarek Sokolowski/AP hide caption

Elon Musk, owner of X, sued the Center for Countering Digital Hate after the group published a series of reports detailing an uptick of hate speech on X, the social media platform formerly known as Twitter.

A federal judge has dismissed X owner Elon Musk's lawsuit against a research group that documented an uptick in hate speech on the social media site, saying the organization's reports on the platform formerly known as Twitter were protected by the First Amendment.

Musk's suit, "is so unabashedly and vociferously about one thing that there can be no mistaking that purpose," wrote U.S. District Judge Charles Breyer in his Monday ruling, "This case is about punishing the Defendants for their speech."

Amid an advertiser boycott of X last year, Musk sued the research and advocacy organization Center for Countering Digital Hate, alleging it violated the social media site's terms of service in gathering data for its reports.

One of the group's findings, published in June, detailed how "racist, homophobic, neo-Nazi, antisemitic or conspiracy content" from paid users went unmoderated on the site.

During a February hearing, lawyers for Musk asked if the suit could be refiled against the research group, but Breyer declined that request. The judge said claiming the alleged data scraping was harming the platform's safety and security does not "make very much sense."

Judge is skeptical of Musk's claims

Researchers with the center say data was compiled using third-party tools that accessed publicly available information, but Musk contended that the group scraped large amounts of data from X without the company's permission, leading to a loss of advertising revenue in the tens of millions of dollars.

Judge skeptical of lawsuit brought by Elon Musk's X over hate speech research

In a February hearing, Breyer appeared highly skeptical of X's arguments. He elaborated on those doubts in his Monday order tossing the suit.

"It is also just not true that the complaint is only about data collection," the judge wrote. "It is impossible to read the complaint and not conclude that X Corp. is far more concerned about CCDH's speech than it is its data collection methods."

Musk, a self-professed free speech absolutist, often says that nearly anything within the bounds of law should be allowed on X. However, Musk himself has been less tolerant of comments and remarks that cast him in a harsh light.

In November, Musk sued another group, the left-leaning nonprofit Media Matters for America, over reports that documented how advertisements from major corporations were appearing alongside antisemitic content on X. The suit, which is still pending, calls the group's reports "a blatant smear campaign."

Musk did not return a request for comment on the Monday ruling, but in an email last month following a hearing in the case, Musk wrote: "Your org is not on X, therefore doesn't exist as far as I'm concerned," referring to NPR's decision last year to leave the platform.

Since the center won under California's so-called anti-SLAPP laws — which protect people and groups from frivolous lawsuits aimed at suppressing free speech — Musk will be on the hook to pay the group's legal fees.

"The specific amount of fees will need to be hashed out in court," said Ben Weich, spokesman for the group.

Musk has brought back previously suspended users to X

In 2022, after Musk purchased Twitter, he suspended the accounts of several journalists who covered Musk's takeover of the site, before reinstating them after a backlash.

Imran Ahmed, the founder and CEO of the Center for Countering Digital Hate, views Musk's suit as the billionaire's latest effort to silence criticism over how he is running the social media site.

"We hope this landmark ruling will embolden public-interest researchers everywhere to continue, and even intensify, their vital work of holding social media companies accountable for the hate and disinformation they host and the harm they cause," Ahmed said.

Since Musk completed his takeover of Twitter in October 2022, he has laid off a majority of its staff and brought back users who were suspended for things like espousing white supremacy and denying the results of the 2020 U.S. presidential election.

He also turned the platform's verification system upside down by allowing users to pay for the once-coveted blue check mark.

Users of X who pay for Musk's premium service, some of them previously kicked off Twitter, have the ability to write longer posts and receive boosted visibility.

Musk has been inconsistent about the state of X's business.

At times, he says the business is strong, but other times, he points to advertising revenue being down 60% and floats the possibility of the company entering bankruptcy proceedings.

Watch CBS News

Judge tosses out X lawsuit against hate-speech researchers, saying Elon Musk tried to punish critics

Updated on: March 25, 2024 / 6:33 PM EDT / CBS/AP

A federal judge on Monday dismissed a lawsuit by Elon Musk's X Corp. against the nonprofit Center for Countering Digital Hate, ruling that the case was about "punishing" the research group for its speech.

The Center for Countering Digital Hate (CCDH) has documented the increase in hate speech on the site since it was acquired by the Tesla owner in 2022. X, formerly known as Twitter, sued the nonprofit last year, claiming the center's researchers violated the site's terms of service by improperly compiling public tweets. 

X argued that the CCDH's reports on the rise of hate speech on the service had cost it millions of dollars when advertisers fled. On Monday, U.S. District Court Judge Charles Breyer dismissed the suit, writing in his order that it was "unabashedly and vociferously about one thing" — punishing the nonprofit for its speech.

In a statement posted to X, the social media platform said it "disagrees with the court's decision and plans to appeal."

Today a federal court in San Francisco issued a decision in the case X brought against the Center for Countering Digital Hate for illegally obtaining platform data to create misleading research. X disagrees with the court's decision and plans to appeal. — News (@XNews) March 25, 2024

It's not the only time Musk's X has sued after a group flagged issues with hate speech on the social media platform. 

Last November, several big advertisers including IBM, NBCUniversal and its parent company Comcast, said that they stopped advertising on X after a report from the liberal advocacy group Media Matters said their ads were appearing alongside material praising Nazis. The report proved to be yet another setback as X sought to win back big brands and their ad dollars, X's main source of revenue. 

In November, X sued Media Matters , alleging that the group was trying to "drive advertisers from the platform and destroy X Corp." 

Later that month, Musk went on an expletive-ridden rant in response to advertisers that halted spending on X in response to antisemitic and other hateful material, saying they are are engaging in "blackmail" and, using a profanity, essentially told them to go away.

Seeking millions from CCDH

In suing the CCDH, X had sought millions of dollars in damages from group, arguing that the nonprofit's reports led to the exodus of advertisers and the loss of ad revenue.

But the judge agreed with CCDH's argument saying X cannot seek damages for the independent acts of third parties based on CCDH's reports, or its "speech."

X had also alleged that the CCDH had "scraped" its site for data, which is against its terms of service. But the judge found that X failed to "allege losses based on technological harms" — that is, the company didn't show how the scraping led to financial losses for X.

The center is a nonprofit with offices in the U.S. and United Kingdom. It regularly publishes reports on hate speech, extremism or harmful behavior on social media platforms like X, TikTok or Facebook. The organization has published several reports critical of Musk's leadership, detailing a rise in anti-LGBTQ hate speech as well as climate misinformation since his purchase.

"Hypocritical campaign of harassment"

Imran Ahmed, the center's founder and CEO, said the lawsuit amounted to a "hypocritical campaign of harassment" by a billionaire who talks about protecting free speech but who then uses his wealth to try to silence his critics. He said the lawsuit shows the need for a federal law requiring tech companies to release more information about their operations, so that the public can understand how these powerful platforms are shaping society.

"We hope this landmark ruling will embolden public-interest researchers everywhere to continue, and even intensify, their vital work of holding social media companies accountable for the hate and disinformation they host and the harm they cause," said Ahmed.

Roberta Kaplan, the center's attorney, said the dismissal of X's suit shows "even the wealthiest man cannot bend the rule of law to his will."

"We are living in an age of bullies, and it's social media that gives them the power that they have today," Kaplan said in an email to reporters. "It takes great courage to stand up to these bullies; it takes an organization like the Center for Countering Digital Hate. We are proud and honored to represent CCDH."

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