whisper
Multilingual speech recognition with 99 languages, transcription, translation, and six model sizes from 39M to 1550M parameters.
- Supports transcription, translation to English, language identification, and word-level timestamps across 99 languages trained on 680,000 hours of audio
- Six model sizes (tiny through large) with configurable speed/quality tradeoffs; turbo model offers 8× speedup over large with comparable quality
- GPU acceleration delivers 10–20× faster processing; CPU transcription available for resource-constrained environments
- Command-line and Python API interfaces; outputs to plain text, SRT subtitles, WebVTT, or JSON with segment timing
- Initial prompt support improves accuracy on technical terms and domain-specific vocabulary; temperature fallback for low-confidence segments
Whisper - Robust Speech Recognition
OpenAI's multilingual speech recognition model.
When to use Whisper
Use when:
- Speech-to-text transcription (99 languages)
- Podcast/video transcription
- Meeting notes automation
- Translation to English
- Noisy audio transcription
- Multilingual audio processing
Metrics:
- 72,900+ GitHub stars
- 99 languages supported
- Trained on 680,000 hours of audio
- MIT License
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