linto-ai/whisper-timestamped

Health v2 · maintenance only

Adoption not part of the score

2841 stars · 211 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library extending OpenAI's Whisper models to produce accurate word-level timestamps and confidence scores during multilingual speech recognition. It uses Dynamic Time Warping on cross-attention weights with no extra inference steps and low memory overhead.

Use cases

• transcribe audio with word-level timestamps
• get confidence scores for each transcribed word
• run speech-to-text on long audio files with low memory
• detect spoken language with confidence
• apply voice activity detection before transcription
• generate subtitles with precise word timing

When to choose

• you need word-level timestamps rather than Whisper's approximate segment timestamps
• you want confidence scores per word or segment
• you want to keep using openai-whisper with minimal changes
• you process long audio files and care about memory usage

When to avoid

• you need speaker diarization as a first-class feature
• you require a non-Python or non-PyTorch environment
• you need a permissively licensed dependency (it is AGPL-3.0)
• you only need coarse segment-level transcription

Facets

library · maturity active

speech-recognition machine-learning deep-learning speech-processing machine-learning python cli cross-platform whisper word-timestamps asr speech-to-text pytorch voice-activity-detection multilingual confidence-scores transcription natural-language-processing

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markdown · JSON · MCP: product_card(name="linto-ai/whisper-timestamped")