What is Speech to Text Technology and Where it is used

Discover the evolution and applications of speech-to-text technology. From business to education, explore how speech recognition is transforming communication. Read more.

While speech-to-text and voice recognition are not new technologies, they have developed significantly over the years. The rise of mobile devices and the proliferation of applications persuaded developers and independent software suppliers to make develop these types of software and functionalities available both on smartphones and tablets. This factor has opened up the use of speech recognition software in an ever-growing range of application scenarios, from business to education.

What is Speech-to-Text or Speech Recognition?

Speech-to-Text or speech recognition is an integrated technology that merges computer science, engineering, and computational linguistics to enable computers to recognize and transcribe spoken words into written text. The vocabulary of rudimentary speech recognition software is restricted, and it can only recognize words and phrases when they are uttered clearly. Comparatively, advanced software can handle natural speech, varied accents, and multiple languages.

Speech-to-text software based on artificial intelligence is employed for hands-free note-taking, live captioning, offering better customer support, and much more. Speech recognition technology is being used to swiftly and effectively create emails, give useful notes as transcripts from meetings and events, and enable accessibility. While voice recognition and speech recognition are sometimes conflated, speech recognition concentrates on the translation of speech from a verbal format to a written format, whereas voice recognition solely aims to recognize the voice of an individual.

How does speech recognition work?

Following these four processes, speech recognition software converts the audio a microphone records into text that both computers and people can comprehend.

  • Analyze and convert the audio into a computer-readable format: Several vibrations are produced when someone speaks. The vibrations are picked up by speech recognition technology , which converts them via an analog-to-digital converter into a digital language.

  • Division or segmentation: An audio file is used as the source for the analog-to-digital converter, which then measures and filters the waves to isolate the desired sounds. Leading this, the sounds are divided into hundredths or thousandths of seconds and matched to phonemes.
  • Phoneme matchingIn any language, a phoneme is a unit of sound that separates one word from another. A mathematical model matches the phonemes to well-known sentences, words, and phrases and then runs them through a network.

  • Text generation: Then, based on the most likely rendition of the audio, the text is generated and shown to the user.

Is it a part of AI and Machine Learning?

The latest voice recognition software uses AI and machine learning techniques like deep learning and neural networks. To process speech, these systems analyze the grammar, syntax, structure, and signal composition of audio and voice signals. Machine learning algorithms are particularly suited for subtleties like accents, since they learn more with each use.

The algorithms and techniques used to provide speech recognition features are powerful. These are a few of them other than AI and ML:

  1. Hidden Markov model

    When a variable is only partially visible or not instantly available to the sensor (with voice recognition and a microphone), HMMs are used in autonomous systems. In acoustic modeling, for instance, software must use statistical probability to match language units to auditory data.

  2. Natural Language Processing

    NLP, a subfield of artificial intelligence, focuses on the interaction between humans and machines through language through speech and text, albeit it isn't always a specific method employed in speech recognition. Speech recognition is a common feature in mobile devices, and it may be used for voice search (like Siri) or to increase texting accessibility.

  3. N-grams

    The simplest kind of language model (LM), known as n-grams, assigns a probability to individual sentences or phrases. A series of N words make up an N-gram. For instance, the words "order the pizza" and "please order the pizza" each has a three-gram or trigram length. Using grammar and the likelihood of particular word combinations helps to increase recognition and precision.

How it is different from Text-to-Speech (TTS)?

Text-to-speech is not the same as speech-to-text. With the use of computational linguistics and robust software, speech-to-text can understand spoken words and convert them to text. Other names for it include computer speech recognition and speech recognition. You may produce lengthy notes, dictations, essays, blogs, and reports with the use of voice-to-text, which offers continuous speech recognition. To share your notes, you can also use your preferred speech recognition software.

Whereas, text-to-speech blends voice with cutting-edge technology, and we have become accustomed to utilizing voice commands and voice recognition to carry out all of our everyday duties. Because text-to-speech software may respond to security questions from telephone banking, it offers several benefits. We can use the program to conduct Internet searches, which is an additional benefit. Text-to-speech enables you to respond to multiple demands and wishes of each user for your services, apps, and content interactive mode, regardless of whether your clients are website visitors, app users, learners, subscribers, or buyers.

Examples of Some Speech Recognition Software


One of the most popular speech recognition software, Briana, can accurately identify over 90 different languages. You may operate applications and translate text on any application or website with this speech recognition technology, which is based on artificial intelligence. The fact that Braina works with Windows, iOS, and Android is the best part. Briana Lite, Briana PRO, and Briana PRO Lifetime are the three versions that are offered. In contrast to the latter two, which need yearly and lifetime subscriptions, the first one is free.


The Nuance company's Winscribe software offers documentation workflow management so users may arrange their content. It works with PC, iPhone, and Android devices. It offers quick, simple, and safe documentation solutions. This approach hopes to provide experts more time to focus on tasks that benefit their company. Winscribe is a speech recognition and document management system designed for professionals in medium and big enterprises.

Google Now

The speech recognition feature of Google Search in the Google App is called Google Now. Both Android and iOS smartphones may use this capability. It works best in Android devices as it is fully integrated with the Android OS and may be used for any task. Google Now may start and close apps, send text messages, and receive calls on Android smartphones. It may perform searches on iOS devices.

Alibaba Cloud Intelligent Speech Interaction

To construct its Intelligent Speech Interaction product, Chinese cloud giant Alibaba employs technologies such as speech synthesis, voice recognition, and natural language understanding. It is currently available in the following languages: Cantonese Chinese, Mandarin Chinese, Japanese, English, French, Korean, and Indonesian are among the languages available, with more on the way.

Google Speech-to-Text API

The powerful ML technology used by Google to power its cloud-based ASR software and API is known as Google Speech-to-Text. It has a library of pre-trained models for different topics and supports over 125 different languages.

Benefits and Applications of Speech Recognition Software

Speech Recognition Software Converting Speech to Text

Speech recognition, like many technologies, offers several advantages that help users to enhance their daily routines.

The primary benefits of using speech recognition software are:


  • Saves Time:By producing correct transcripts in real-time, automatic speech recognition technology saves time.

  • Cost-effective: While some programs are free, most speech recognition software requires a monthly membership. However, paying for a subscription is far less expensive than using human transcribing services.

  • Boosts audio and video quality: Speech recognition features allow audio and video data to get transformed in real-time for quick video transcription and subtitling.

  • Better experience: Streamlines the client experience by utilizing natural language processing to make it simpler, more smooth, and more accessible.

Some applications of speech recognition software include:

  • Education: Language training makes use of speech recognition technologies. When a person speaks, the program may hear them and provide pronunciation help.

  • Customer Service: Customer inquiries are answered by automated voice assistants, who also give useful information.

  • Medical or Healthcare applications: Customer inquiries are answered by automated voice assistants, who also give useful information.

  • Accessibility for the DisabledA person with hearing loss can understand what is being said by using closed captions and speech recognition software to convert spoken words into text. Those who have trouble using their hands or speech recognition software can use voice commands rather than typing to interact with computers.


Speech recognition is a rapidly developing technology. It is one of several methods for communicating with computers that require little or no typing. A wide range of communications-based business applications benefits from the ease and speed of spoken communication enabled by this technology. Speech recognition software has come a long way in the last 60 years. They are still becoming better, especially thanks to AI.

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