Best Free Speech-To-Text APIs and Open Source Libraries

Introduction

Are you interested in converting speech to text for your own project but unsure where to begin? Look no further! In this article, we will explore the best free speech-to-text APIs and top open-source libraries for speech recognition. While converting speech to text is an exciting challenge, existing solutions can make it easier.

Options for Speech Recognition

When it comes to speech recognition, you generally have two options: APIs and open-source libraries. Each has its advantages and disadvantages.

APIs

Using an API is often the quickest way to get started. You won’t need in-depth knowledge of deep learning or the underlying model, as APIs typically provide state-of-the-art trained language models. This means higher accuracy and features like entity detection and sentiment analysis right out of the box.

However, there are downsides to using APIs:

• Cost: While many APIs offer a free tier, you will need to pay for additional usage.
• Internet dependency: You must have an internet connection to access these services.

Recommended APIs

1. Google Speech to Text API

   • Popular for its high accuracy and supports over 60 languages.
   • Free tier: 60 minutes of transcription per month + $ 300 in free credits for new users.
   • Pricing: $ 0.006 per 15 seconds or $ 0.009 depending on options.
   • Complicated setup; requires a Google Cloud account.

2. Assembly AI

   • Developer-friendly API with great documentation and tutorials to ease integration.
   • Free tier: 3 hours of audio transcription per month.
   • Pricing: $ 0.00025 per second (approx. $ 0.00375 per 15 seconds).
   • Currently supports only English but offers additional features like sentiment analysis.

3. AWS Transcribe

   • Offers one hour of transcription free per month for the first year.
   • Pricing: $ 0.024 per minute (same as Google).
   • Setup can be complex, but offers specialized features like medical transcription.

Open Source Libraries

If you prefer a completely free option, open-source libraries are a great choice. They allow you to see the underlying code and contribute improvements.

However, setting up open-source libraries can be challenging:

• Lack of resources: Often requires a good GPU and programming skills.
• Complex setup: Many libraries necessitate a Linux build environment.

Recommended Libraries

1. Deep Speech

   • Developed by Baidu; works offline on various devices.
   • Uses TensorFlow and has decent out-of-the-box accuracy.

2. Kaldi

   • A widely popular speech recognition toolkit in the research community.
   • Allows for custom model training; implemented in C++.

3. Wave 2 Letter

   • From Facebook AI, now part of the Flashlight project.
   • Good accuracy for small projects and has user-friendly documentation.

4. SpeechBrain

   • A PyTorch-based all-in-one toolkit for conversational AI.
   • Simplifies the setup process and integrates well with Hugging Face.

5. Coqui STT

   • A fast multi-platform deep learning toolkit for speech-to-text models.
   • Supports over 20 languages and is effective in both research and production settings.

Keyword

• Speech-to-text
• APIs
• Open-source libraries
• Google Speech to Text
• Assembly AI
• AWS Transcribe
• Deep Speech
• Kaldi
• Wave 2 Letter
• SpeechBrain
• Coqui STT

FAQ

Q: Which speech-to-text API is the easiest to set up?
A: Assembly AI is regarded as the easiest due to its user-friendly documentation and quick integration.

Q: Do I need to pay for using these APIs?
A: Most APIs have a free tier, but you may incur costs if you exceed the limits.

Q: Are open-source libraries completely free to use?
A: Yes, open-source libraries are free, but they may require computational resources and technical skills for setup.

Q: Is there any speech recognition library that works offline?
A: Yes, Deep Speech is designed to run offline and provides decent out-of-the-box accuracy.

Q: Can I contribute to open-source libraries?
A: Absolutely! Open-source libraries allow you to see their underlying code and contribute improvements.

This article provides an overview of the best free methods for speech-to-text conversion. Depending on your needs and expertise, you can choose between an API or an open-source solution. Happy coding!