What is the app that turns voice into text?

Voice-to-text apps, also known as speech-to-text apps, are software applications that allow users to speak into a microphone and have their speech converted into written text in real-time. These apps utilize advanced speech recognition technology and artificial intelligence to transcribe the human voice quickly and accurately.

In general, voice-to-text apps work by breaking down the audio input into phonemes, analyzing the phonetic components, and using predictive text algorithms to determine the most likely words and sentences being spoken. As the user continues talking, the app continues refining and correcting the output text.

Some of the most popular voice-to-text apps include Google Voice Typing on Android, Voice Memos on iOS, and third-party apps like Otter.ai and Speechnotes.

Voice-to-text apps have many use cases, including drafting documents, taking notes, writing emails or messages hands-free, transcription, accessibility, and more. They can save time and effort while also enabling multi-tasking for people whose hands are occupied by other tasks.


The origins of voice recognition technology date back to the 1950s and 1960s when researchers at Bell Laboratories developed systems that could recognize digits spoken by a single speaker (Source). In 1962, IBM demonstrated a “Shoebox” machine that could recognize 16 words spoken in English. Throughout the 1960s and 70s, researchers continued to make incremental advances in developing systems that could recognize limited vocabularies from a single speaker.

A major milestone was reached in the 1980s when Dragon Systems introduced the first commercial large-vocabulary speech recognition program called Dragon Dictate in 1990. This allowed users to dictate text at speeds up to 160 words per minute with a vocabulary of up to 30,000 words (Source). In 1997, Dragon released Dragon NaturallySpeaking which brought continuous speech recognition to the PC. This laid the groundwork for modern voice-to-text apps.

In the late 1990s and early 2000s, voice recognition expanded beyond desktop software to telephone-based systems. Companies began offering voice transcription services that utilized human transcribers with speech recognition software support. The release of smartphones then opened the door for voice-to-text apps like Siri that users could access anywhere (Source).

How Voice-to-Text Apps Work

Voice-to-text technology relies on advanced artificial intelligence and machine learning to convert speech into text. The main components involved are:

Speech recognition – This takes the acoustic signals from speech and converts them into digital representations that can be processed by a computer. Algorithms analyze the speech signals to identify phonemes, syllables, and words. Statistical models and neural networks have enabled speech recognition systems to become extremely accurate at transcribing speech.

Natural language processing – This analyzes the syntactic and semantic structure of speech to extract meaning. Things like grammar, punctuation, capitalization, and sentence structure are interpreted to convert the speech into coherent, readable text. Contextual analysis helps determine the intended meaning of ambiguous words or phrases.

AI and machine learning – Large datasets of speech samples are used to train machine learning models to continually improve speech recognition and language processing. The more data the models are exposed to, the better they become at converting all types of speech into accurate text transcription. AI techniques like deep learning enable voice-to-text apps to handle nuances of natural speech.

By combining these key technologies, voice-to-text apps can process speech signals in real-time and output highly accurate text. The latest systems are extremely good at handling accents, dialects, slang, and colloquial speech. However, some errors and inaccuracies may still occur, especially with technical terms or proper nouns.


Speech-to-text technology provides many benefits for users. According to the Mindshift article, “The Benefits of Speech-to-Text Technology in All Classrooms,” by Katrina Schwartz, speech-to-text tools enhance accessibility for students who struggle with writing or have disabilities (Schwartz, 2021). The technology allows them to get their ideas down quickly without the physical act of typing or writing, improving their communication skills.

Speech-to-text apps are also more convenient and can improve productivity. The article “12 Benefits of Speech to Text” by Dataworxs states that voice typing eliminates illegible handwriting and allows for quicker document turnaround without being tied to a keyboard (Dataworxs, n.d.). Users have the flexibility to speak their thoughts and compose documents whether in the office or on the go.

Another major benefit is the ability to use devices hands-free. As listed on SmarterToolsforTeachers.org, students can “produce legible text” by speaking rather than typing or writing by hand. This allows for multitasking and is especially helpful for those with physical disabilities (SmarterToolsforTeachers.org, n.d.).

Finally, speech-to-text apps provide much faster documentation. Thoughts can be captured at nearly the speed of natural speech versus typing speed. This saves time for all users and helps those who may forget ideas in the time it takes them to write manually.


Despite the convenience of voice-to-text software, there are some key limitations to be aware of:

Background noise issues – These apps often struggle with background noise, making transcription errors more likely in noisy environments. Even ambient sounds like an air conditioner or traffic can throw off transcription accuracy (see https://podcastle.ai/blog/the-pros-and-cons-of-voice-to-text/).

Accent and dialect challenges – Apps trained on standard dialects may not understand regional accents or non-native accents very well. For example, “y’all” may get transcribed as “you all” or Spanish accents can lead to more errors (see https://www.rev.com/blog/speech-to-text-technology/advantages-and-disadvantages-of-speech-recognition-software).

Privacy concerns – Some apps record and store audio in the cloud, raising privacy issues. Users should understand if and how their voice data is being used (see https://www.britishlegalitforum.com/news/what-are-the-limitations-of-speech-to-text/).

Transcription errors – No system is 100% accurate. Errors like dropped words, punctuation mistakes, and incorrect homophones happen, requiring editing or proofreading after transcription.

Popular Voice-to-Text Apps

There are several popular and highly rated voice-to-text apps available across platforms. Some of the top options include:

Google Voice Typing – This free app from Google allows real-time voice transcription in Google products like Docs, Gmail, and more. It’s built into Android devices and available on iOS as well. Google Voice Typing leverages Google’s powerful speech recognition technology to provide fast, accurate transcriptions (Source).

Otter.ai – Otter is a top-rated app that transcribes voice conversations, meetings, interviews, lectures, and more in real-time. It’s available on mobile and integrates with services like Zoom, Teams, and Google Meet. Otter provides searchable, shareable transcripts and is popular for business and academic use (Source).

Speechnotes – This web-based app offers free voice transcription with no time limits. It works offline after initial setup and has robust formatting options ideal for writing long-form documents. Speechnotes automatically saves audio and text to the cloud (Source).

Dragon Anywhere – From Nuance, Dragon Anywhere provides professional-grade voice transcription on mobile devices. It adapts to the user’s voice over time for higher accuracy. The app is best suited for dictating notes, messages, documents, and filling out forms on the go (Source).

Windows Speech Recognition – Microsoft’s built-in Windows Speech Recognition tool allows dictation and voice commands on Windows PCs. It can transcribe documents, email, forms, and more with robust customization options. Windows Speech Recognition works fully offline after initial setup (Source).

Use Cases

Voice-to-text apps have a variety of use cases that demonstrate their versatility and convenience. Some of the most popular use cases include:

Note-taking: Voice-to-text apps like Otter.ai allow students and professionals to record lectures, meetings, or conversations and receive an automated transcription. This is useful for notetaking when you don’t have time to type everything out.

Messaging: Apps like Siri and Google Assistant allow hands-free messaging by transcribing your voice messages to text before sending them. This makes messaging more convenient when your hands are occupied.

Emails: Similar to messaging, voice-to-text can be used to dictate emails when you are unable to type. This helps maximize productivity.

Documents: For longer documents, voice dictation can be less tedious and faster than manual typing. Apps like Google Docs integrate voice typing to transcribe your speech into text within documents.

Accessibility aid: For those unable to use their hands to type, voice transcription apps provide essential accessibility, allowing them to communicate through writing.

Hands-free tasks: When your hands are occupied with cooking, driving, or other activities, voice-to-text allows you to transcribe speech without typing.

Future Outlook

Voice-to-text technology is expected to improve significantly in the coming years. Some key advancements on the horizon include:

  • Improvements in accuracy: Speech recognition systems will become even better at accurately transcribing speech into text. This will be driven by advances in deep learning and AI. Accuracy for diverse accents and noisy environments is also expected to improve.
  • Integration with more services: Voice-to-text will likely become integrated into more applications, devices, and services beyond just standalone apps. For example, virtual assistants, wearables, vehicles, and smart home devices will likely adopt the technology.
  • Wider language support: Systems will expand to support a greater variety of languages beyond just English. This will increase accessibility for non-native English speakers.
  • On-device processing: More processing will likely happen directly on devices rather than in the cloud. This will increase speed, enable offline use, and enhance privacy protections.

As voice-to-text continues to advance, it has the potential to become an even more seamless and ubiquitous technology integrated into everyday life. The improvements will likely make these apps more convenient, customizable, and helpful for users across languages, demographics, and needs. This could lead to new use cases and adoption by wider audiences in the years to come.

Tips for Effective Use

To get the most out of voice-to-text apps, follow these tips:

Speak clearly and naturally. Enunciate your words, but don’t overdo it. Talk at a steady pace in your normal speaking voice. Apps can have a hard time with mumbled or shouted speech.

Reduce background noise. Find a quiet environment or use headphones to minimize interfering sounds. Noise makes it harder for the app to understand you.

Learn voice commands. Many apps have special commands to insert punctuation, capitalize words, delete text, and more. Using commands saves time correcting errors.

Correct errors promptly. Fix any incorrect transcriptions right away so the app learns how you speak. This improves accuracy over time.

According to Alvarez (https://www.alvareztg.com/wisdom-wednesday-tips-and-tricks-voice-to-text-apps/), “Talking too fast causes voice to text applications to misunderstand your words. Enunciate clearly as you speak naturally into your phone’s microphone.”


Voice-to-text apps have come a long way in recent years thanks to advancements in artificial intelligence and natural language processing. These apps allow us to dictate speech and convert it to text quickly and accurately. While they still have some limitations, voice-to-text apps offer many benefits for productivity, accessibility, and convenience.

In summary, the key points about voice-to-text apps covered in this article include:

  • They have a decades-long history evolving from early dictation systems to present-day AI
  • They utilize speech recognition technology to analyze spoken words and convert them to text
  • Benefits include saving time, boosting productivity, enabling hands-free work, and aiding those with disabilities
  • Limitations exist around accuracy, privacy, and requirement of internet connection
  • Popular apps include built-in options like Siri and Google Assistant as well as third-party apps like Otter.ai
  • Use cases span the productivity, accessibility, education, journalism, business, and creative spheres

Looking ahead, voice-to-text technology will likely continue improving and find widespread adoption across many facets of daily life. With the convenience and capabilities these apps provide, they are well worth exploring and utilizing where applicable. Just be sure to set proper expectations around accuracy and be aware of any potential privacy tradeoffs. But overall, voice-to-text represents an exciting step forward in transcribing the spoken word efficiently in our digital world.

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