Whisper offers five model sizes, each with different memory requirements and inference speeds. The models can be used for English-only applications or multilingual applications. The model's performance varies depending on the language. It can be used to transcribe speech in audio files and can also translate non-English speech into English. The model can be used within Python, and it provides lower-level access to detect the spoken language and decode the audio. The code and model weights of Whisper are released under the MIT License.
Key takeaways:
- Whisper is a general-purpose speech recognition model developed by OpenAI, capable of multilingual speech recognition, speech translation, and language identification.
- The model is trained using a Transformer sequence-to-sequence approach on various speech processing tasks, allowing it to replace many stages of a traditional speech-processing pipeline.
- Whisper offers five model sizes, each with different speed and accuracy tradeoffs, and the English-only models tend to perform better.
- Whisper's code and model weights are released under the MIT License, and it can be used both from the command line and within Python.