whisperX and whisper-diarization

WhisperX extends Whisper with optimized word-level timestamps and integrated diarization capabilities, while whisper-diarization is a standalone diarization wrapper around base Whisper, making them competitors offering similar speaker attribution features with different implementation approaches.

whisperX
80
Verified
whisper-diarization
56
Established
Maintenance 20/25
Adoption 15/25
Maturity 25/25
Community 20/25
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 20/25
Stars: 20,758
Forks: 2,188
Downloads:
Commits (30d): 11
Language: Python
License: BSD-2-Clause
Stars: 5,437
Forks: 500
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: BSD-2-Clause
No risk flags
No Package No Dependents

About whisperX

m-bain/whisperX

WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

This tool helps you accurately transcribe audio recordings, providing not just the words but also precise timestamps for each word. It can also identify who is speaking at any given time, separating conversations by speaker. Anyone who needs highly accurate transcripts for audio analysis, subtitling, or content review would find this useful, such as researchers, journalists, or content creators.

audio-transcription speech-to-text speaker-diarization subtitling qualitative-research

About whisper-diarization

MahmoudAshraf97/whisper-diarization

Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper

This tool helps you automatically transcribe audio recordings and identify who said what. You provide an audio file, and it delivers a text transcript where each sentence is attributed to a specific speaker. This is useful for anyone needing to analyze conversations, meetings, or interviews, such as researchers, journalists, or content creators.

meeting-transcription interview-analysis audio-to-text speaker-identification podcast-transcription

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