Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data. This open-source toolkit includes a pre-trained ASR and speech synthesis model, which can be finetuned with additional data for better accuracy.
One of the benefits of using Whisper is its easy integration with existing systems. The model has been released under the MIT License, meaning it can be customized and improved to meet your specific needs. For example, Amazon CodeWhisperer is an AI coding companion that generates whole-line and full-function code suggestions in your IDE to help you get more done faster.
To start with Whisper, check out the GitHub page for the code and model weights. If you want to evaluate Whisper Medium on LibriSpeech, you can use this code snippet. Additionally, AssemblyAI provides a helpful tutorial for running the Whisper model.
Overall, Whisper makes speech recognition easier and more accessible for developers and researchers. It’s open-source code and customizable model makes it a great tool for enhancing speech recognition capabilities. Check it out and let us know what you think!
