WhisperX

Recall.ai - Meeting Transcription API

If you’re looking for a transcription API for meetings, consider checking out [Recall.ai's Meeting Transcription API](https://www.recall.ai/product/meeting-transcription-api?utm_source=github&utm_medium=sponsorship&utm_campaign=mbain-whisperx), an API that works with Zoom, Google Meet, Microsoft Teams, and more. Recall.ai diarizes by pulling the speaker data and separate audio streams from the meeting platforms, which means 100% accurate speaker diarization with actual speaker names.

This repository provides fast automatic speech recognition (70x realtime with large-v2) with word-level timestamps and speaker diarization.

• ⚡️ Batched inference for 70x realtime transcription using whisper large-v2
• 🪶 faster-whisper backend, requires <8GB gpu memory for large-v2 with beam_size=5
• 🎯 Accurate word-level timestamps using wav2vec2 alignment
• 👯‍♂️ Multispeaker ASR using speaker diarization from pyannote-audio (speaker ID labels)
• 🗣️ VAD preprocessing, reduces hallucination & batching with no WER degradation

**Whisper** is an ASR model [developed by OpenAI](https://github.com/openai/whisper), trained on a large dataset of diverse audio. Whilst it does produces highly accurate transcriptions, the corresponding timestamps are at the utterance-level, not per word, and can be inaccurate by several seconds. OpenAI's whisper does not natively support batching.

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