m-bain/whisperX

Health v2 · maintenance only

Adoption not part of the score

24736 stars · 2497 forks observed · 2026-10-21

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

WhisperX is a Python library providing fast automatic speech recognition with word-level timestamps and speaker diarization. It combines Whisper-based batched inference (up to 70x realtime), wav2vec2 forced alignment for accurate word timings, VAD preprocessing, and pyannote-audio speaker labeling.

Use cases

• transcribe audio files with word-level timestamps
• add speaker labels to meeting or interview transcripts
• run fast batched speech-to-text on GPU
• reduce Whisper hallucinations with voice activity detection
• align existing transcripts to audio at phoneme level
• diarize multi-speaker recordings

When to choose

• you need per-word timing accuracy beyond Whisper's utterance-level timestamps
• you want fast GPU transcription with batching and a memory-efficient backend
• you need speaker diarization integrated into the ASR pipeline

When to avoid

• you need a hosted transcription API with real speaker names from meeting platforms
• you only need rough utterance-level transcripts and want a simpler setup
• you have no GPU and need maximum throughput

Facets

library · maturity active

speech-recognition machine-learning audio-processing speech-processing machine-learning python cli asr whisper word-level-timestamps speaker-diarization forced-alignment transcription faster-whisper wav2vec2 pyannote audio gpu

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markdown · JSON · MCP: product_card(name="m-bain/whisperX")