Best Audio to Text APIs (2022)

Table of Contents

audio to text

What is Speech-to-Text?

Speech-to-text (STT) allows for the real-time transcription of audio streams into text. This is also called computer speech recognition.

This type of speech recognition software is extremely useful for anyone who needs to generate a large amount of written content quickly and easily. It is also useful for people who have disabilities that make using a keyboard difficult.

What is a Speech-to-Text API?

A speech-to-text application programming interface (API) is the ability to invoke a service that converts audio into written text. 

The audio to text service will process the provided audio file using machine learning or a set of tools that combines machine learning with rule-based approaches, and then provide a transcript of what it thinks was said.

What are Important Features of Speech-to-Text APIs

Each API’s key features differ, therefore your use cases will determine your priorities and needs in terms of which features to focus on. Then, you can choose the suitable API for your needs. Some features of speech-to-text APIs are:

  • Accurate Transcription – the most important thing whatever you are using speech-to-text for. For readable transcriptions, the absolute baseline accuracy is 80%.
  • Support for multiple languages – If you intend to work with multiple languages or dialects, this should be a top priority. 
  • Topic detection – If you’re looking to process large amounts of audio in order to better understand what’s being said, an STT API with topic detection may be something to consider.
  • Custom vocabulary – Being able to define custom vocabulary is beneficial if your audio contains a large number of custom terms.
  • Keyword boosting –  allows you to increase the likelihood that the STT API will predict words in your audio that are particularly important or common.
  • Multiple audio formats – A Speech-to-text API that eliminates the need to transcode audio from diverse sources can save you time and money.
  • Profanity filtering – If you’re utilizing STT for community moderation, you’ll require a program that automatically censors or flags profanity in its output.
  • Real-time streaming – If you want to use STT to build truly conversational AI that responds to customer inquiries in real time, you’ll need to use a STT API that returns results as quickly as possible.

Why use speech-to-text APIs?

Some of the benefits of speech to text APIs are:

Boosting productivity and efficiency

Typing large articles, documents, presentations, etc. manually is laborious. Use a speech-to-text API to transcribe your words. It makes work easier and faster while giving your hands a break.

Reliability

The use of a good speech-to-text API yields high accuracy. As a result, you can rely on these solutions to create documents and papers faster and with fewer errors.

It also aids in multitasking. As a result, always use a highly accurate speech-to-text API, such as Rev.ai, which has an accuracy rate of 84%.

Saved Time

Manually writing heavy text requires not only effort but also a significant amount of time. Speaking is faster than writing, so using speech to text APIs will save you a lot of time. 

It is also extremely beneficial for professionals with slow or average writing speeds. As a result, you can submit your work more quickly and save time.

Decreased Effort

Manually typing long articles takes a long time and wears out your hands. You can save time by using a speech-to-text API instead of typing, and you won’t have to exert any physical effort.

Helping People with Physical Disabilities

People with certain physical disabilities, such as dyslexia or trauma, may have difficulty using well-known devices and input formats, such as keyboards.

Using speech-to-text APIs, they can input words using their own voice rather than typing them manually. Thus making things easier for them and increase their productivity.

Which are the Best Audio to Text APIs? 

Here are some options for the best speech-to-text API for your business or personal use.

1. Amberscript

It produces custom ASR models based on your requirements and allows you to easily integrate them with your software for real-time audio and video files, human-perfected texts, and phone calls.

Pros:

  • Easy adoption to Multi-Language
  • Good scalability

Cons:

  • Limited support
  • High cost

2. AssemblyAI

AssemblyAI’s speech-to-text APIs automatically convert audio and video files and audio streams to text and aid in proper comprehension. 

Pros:

  • High accuracy for non-technical US English
  • Low cost

Cons:

  • Difficulty with lots of terminology, jargon, and accents
  • Slow speed
  • Limited customization

3. AWS Transcribe/ Amazon Transcribe

Amazon Transcribe is a consumer-oriented product developed in conjunction with the Alexa voice assistant.

Pros:

  • Brand name
  • Easy to integrate if you are already in the AWS ecosystem
  • Good choice for short audio for command and response
  • Fairly good accuracy with consumer audio
  • Good scalability, except for costs

Cons:

  • Poor accuracy with business audio or audio with lots of terminology
  • Slow speed
  • Limited support
  • Cloud deployment only
  • High cost

4. Deepgram

Deepgram provides comprehensive deep learning model that enables businesses to achieve faster, more accurate transcription, resulting in more reliable data sets — on-premises or in the cloud.

Pros:

  • Highest out-of-the-box and tailored model accuracy
  • Fastest speed
  • High customization within days
  • Easy to start with Console

Cons:

  • Fewer languages than big tech ASR

5. Google Cloud Speech

It provides an excellent user experience by accurately captioning your speech. Google Cloud Speech also aids in the improvement of your services through the insights gained and transcribed from customer interactions.

Pros:

  • Brand name
  • Easy to integrate if you are already in the Google ecosystem
  • Good choice for short audio for command and response
  • Good scalability, except for costs

Cons:

  • Poor accuracy with business audio with lots of terminologies
  • Slow speed
  • No support
  • High costs

6. IBM Watson Speech to Text

It enables accurate and fast speech recognition in multiple languages for a variety of applications such as customer self-service, speech analytics, agent assistance, and more.

Pros:

  • Brand name

Cons:

  • Poor accuracy
  • Slow speed
  • No self-training
  • Slow customization

7. Rev.ai

With Rev.ai’s API, you can get real-time speech transcription and recognition. Furthermore, Rev supports live speech-to-text streaming for live captions.

Pros:

  • Fast customization
  • Ease of Use
  • Low cost

Cons:

  • Long time to type up an audio