How AI-Powered Speech-To Text & Voice Recognition Revolutionized World?

AI technology and machine learning have come a long way in powering different technologies. More than 70% of consumers reported […

AI technology and machine learning have come a long way in powering different technologies. More than 70% of consumers reported they use special assistance in shopping and in finding things online. You might be aware of voice assistants like – Google Assistant and Alexa.

But do you know that these gadgets use speech-to-text powered by AI? Speech recognition is overcoming the challenges of accents, dialects, and context. The AI-powered speech recognition provides more than 90% of accuracy as compared to traditional models. The best part is; it has now become the most acceptable form of communication in large companies. The majority of search engines have adopted voice technology.

What is speech recognition?

In speech recognition, the computers may take input from different sound vibrations that are available. It uses the analog to digital converter, which uses the other sound waves. Then, it is converted into a digital format that only the computer understands.

All the complex algorithms run on the data, which recognize the speech and return a text result. At times, the data is also converted into a different form. For example, with the use of Google voice typing, the data converts to text. Advanced speech recognition also comprises voice recognition where the system can identify the speaker’s voice.

Why Do We Need Speech Recognition Capabilities?

The important features of speech recognition include-

  • Speaker label – Output is a record, which cites or tags each speaker’s recordings to a multi-participant conversation.
  • Profanity filter- Use filters to identify the positive language or different long phrases, and sanitize speech output.
  • Acoustics training- Attend to the acoustical side of the said production. Train the system to become accustomed to an audio background and speaker styles (like voice pitch, volume, and velocity).

Speech Recognition and AI

The unexpected change of human speech has made expansion challenging. It’s known to be the most difficult computer science area – linguistics, stats, and math.

They are made up of a few components: the speech input, element vectors, decoder, and a quality extraction, word output. It leverages different acoustic forms, an articulation glossary, and speech models to conclude the suitable output.

Speech recognition technology has its accuracy rate, i.e. Word Error-Rate (WER), and speed. Several factors can impact Word Error Rate, such as articulation, tone of voice, pitch, and volume.

Hidden Markov Models (HMM):

Another model – Hidden Markov Models, which is built on the same frame that stipulates that the chance of a state hinge on the existing state, not its prior states.

While it is practical for observable events, such as text inputs, it allows us to incorporate hidden events, such as speech tags, into a futuristic model. They are utilized as different succession models within speech recognition, transfer labels to each unit—i.e. vocabulary, syllables, and phrases—in the sequence.

N-grams: It is the best type of Language Model (LM) that helps to convert possibility to long sentences or expressions. An N-gram is known as a series of N-words. For instance, “order the cheese pizza” is a trigram or 3-gram, and “please order the cheese pizza” is a 4-gram.

Speaker Diarization (SD):

Speaker diarization analytics spot and segment speaker’s identity. It helps programs better distinguish individuals in a formal discussion and is frequently applied at companies that work for call centers distinguishing clients and sales mediators.

Sentence structure and prospects of certain word series can be used to improve the accurateness.

Neural systems:

Primarily leveraged intended for deep learning algorithms charts, the networks process teaching statistics by mimicking the interconnectivity of the individual’s brain via nodes. Each node is made up of some important input, power, a bias (or brink), and productivity.

If that output value is more than a given brink, it “fires” or sets off the node, passing data to the next network layer. Neural networks discover this mapping function during controlled learning and adjust on the loss purpose through the process of gradient descent.  While these are more precise and can recognize more data, this comes at the cost of a routine competence.

5 Best APIs for Speech-To-Text

There are numerous web-enabled speech-to-text APIs that can be used for your app or website. Let us find out some of the most helpful APIs for voice search.

  1. Google Speech-To-Text


  • Identifies 120 languages
  • Offers better accuracy through machine learning models
  • Automatic language recognition
  • Text transcription
  • Recognizes proper noun
  • Data privacy
  • Noise cancellation for phone and video calls
  • Costs money
  • Has a limit to building custom vocabulary
  1. Microsoft Cognitive Services


  • Enhance data security via voice-recognition algorithms
  • Real-time transcription
  • Real-time translation
  • Customizable vocabulary
  • Text-to-speech capabilities for natural speech patterns
  • Built-in constraints due to the API being created for general purposes
  • Uses microservices, which can help solve individual problems but falls short for more significant problems
  1. Dialogflow (Formerly API.AI, Speaktoit)


  • Free, easy to set up, and use
  • Easily integration with a variety of software and web services
  • It can also integrate with devices like Amazon’s Alexa, which are not by Google
  • Unable to handle math functions
  • Unable to equate context with common phrases
  • Unable to create clickable links in the text box
  1. IBM Watson


  • Processes required data in large quantities
  • The assistant that overcomes human limitations
  • Great experience and productive output by conveying appropriate data
  • Easy to set up and use
  • No support for structured data
  • Costlier and requires maintenance
  • The support is available for a limited number of languages
  • Requires prior training to utilize all resources
  1. Speechmatics


  • Fast and easy to use
  • Better accuracy
  • Supports multiple languages and English variants
  • Supports Multi-speaker and file formats
  • Noise cancellation as well as Speaker recognition
  • Can be integrated through REST API
  • Used for cloud service transcription
  • It has no app-based interface
  • Every query costs money

10 of Best Voice-Recognition Software

Here is a list of best transcription and voice recognition software:

  1. Dragon Anywhere

It provides you a Cloud speech recognition tool and you can access the versions of the documents from a mobile phone. This application will allow you to save it to Evernote. Different document layouts like RTF, and text .rrtfd, are also supported.


  • Suitable for iOS users
  • Free trial available for seven days
  • Tasks like document saving on a Cloud, or importing the existing or email, voice can do it. It provides encryption to all your communications
  • Security features like encryption for communication channels
  • No personal information is required
  • It allows you to add more words
  1. Google Now

Google Now is a functionality of the Google App.


  • This can be used for Android and iOS devices. Though it is accessible in iOS, it works best on Android.
  • Google Now is used for making and receiving calls, text messages and for opening and closing the app.
  • For iOS devices, it can be used as an intermediate for search
  1. Siri

Siri is the virtual assistant for Apple devices that supports 21 languages. It comes pre-installed on iOS and replies in its voice.


  • Suitable for iOS devices
  • It is capable of making a call to someone and can send text messages
  • It gives you information on who is making a call to you
  • It can be used to set alarms, timers, and reminders
  1. Cortana

Cortana is a free virtual assistant that comes with Windows 10 systems and Windows phones and for Android and iOS devices.


  • Best suited for Windows users.
  • Supported English, French, German, Italian, Japanese, Chinese, and Spanish.
  • Composing and sending a text message
  • Updating the calendar, reminders, and to-do-lists
  • Music playing
  • Checking the weather
  1. Google Cloud Speech API

This software can recognize 120 languages and offers free video speech recognition for 0-60 minutes. Speech recognition and Video Speech Recognition are free for up to a minute. Up to 1 million minutes, speech recognition can be used at a rate of $0.006 per 15 seconds. In using video recognition, it is available at a rate of $0.012 per 15 seconds. The price depends on different systems.


  • Google Cloud Speech API is used for videos of shorter and longer durations
  • It is used for processing real-time and pre-recorded audio streaming
  • It can translate nouns, dates, and phone numbers automatically
  • It can filter the incorrect content
  • It is accurate in transcribing punctuation
  • It can identify the spoken language
  1. Amazon Lex

This software is used for developing a conversational interface, i.e., Chatbot.


  • It can be integrated with AWS Lambda enabling the apps to trigger the functions and retrieve the data
  • Supports multi-turn conversations
  • Offers 2 kinds of prompts- error handling & confirmation prompt
  • Can apply versioning to Intents, Slot Types, and Bots created by you
  • It provides telephony audio support up to 8 kHz
  1. Microsoft Bing Speech API.

Microsoft speech recognition API transcribes speech into text. The API displays the text through the application and responds as per the command. You can do this text-to-speech conversion in many different languages.


  • Improved accuracy and easy to use
  • It supports more than 14 languages for dictation and 5 languages for conversion mode
  • Beneficial for continuous real-time recognition
  • It is great for interactive, exchange, and transcription scenarios
  1. Voice Finger

Best suited for customizable command capability and can be downloaded for free. However, the full version is available for a price of $9.99. Using the Voice Finger feature, you can control the computer through voice without using a keyboard and a mouse.


  • Let’s you control the mouse and keyboard
  • Support for Windows speech recognition commands
  • Can perform tasks with zero computer contact
  1. Dragon Professional or Dragon for PC

It is one of the best dictation and voice recognition software that can be used for work and personal purposes.


  • Dragon Home lets you perform routine tasks like dictating homework assignments, sending emails, and surfing the web
  • Dragon Professional Individual lets office workers and small businesses create and transcribe documents, insert a signature, or customize the vocabulary
  • It can be synced with Dragon Anywhere
  • Dragon Legal Individual assists legal professionals in streamlining the legal documentation
  1. Google Docs Voice Typing

It integrates with Google Suite, pairs with transcription and voice recognition services.


  • Suitable for dictation on Google Docs
  • A cost-effective solution
  • Supports 43 languages
  • The cursor movement is possible anywhere around the document by using the “go to the end of the document” command

Bottom Line 

Every voice recognition software or Speech-To-Text APIs has different features. So, this software or APIs should not be considered as products offering services, but as a toolbox with features.

Each software has advantages and disadvantages. You must choose the right software or toolkit for your use. This depends on the reason and your organization’s requirements.

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