whisperx

Maintainer: victor-upmeet

Total Score

128

Last updated 5/23/2024
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Paper LinkView on Arxiv

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Model overview

whisperx is a speech transcription model developed by researchers at Upmeet. It builds upon OpenAI's Whisper model, adding features like accelerated transcription, word-level timestamps, and speaker diarization. Unlike the original Whisper, whisperx supports batching for faster processing of long-form audio. It also offers several model variants optimized for different hardware setups, including the victor-upmeet/whisperx-a40-large and victor-upmeet/whisperx-a100-80gb models.

Model inputs and outputs

whisperx takes an audio file as input and generates a transcript with word-level timestamps and optional speaker diarization. It can handle a variety of audio formats and supports language detection and automatic transcription of multiple languages.

Inputs

  • Audio File: The audio file to be transcribed
  • Language: The ISO code of the language spoken in the audio (optional, can be automatically detected)
  • VAD Onset/Offset: Parameters for voice activity detection
  • Diarization: Whether to assign speaker ID labels
  • Alignment: Whether to align the transcript to get accurate word-level timestamps
  • Speaker Limits: Minimum and maximum number of speakers for diarization

Outputs

  • Detected Language: The ISO code of the detected language
  • Segments: The transcribed text, with word-level timestamps and optional speaker IDs

Capabilities

whisperx provides fast and accurate speech transcription, with the ability to generate word-level timestamps and identify multiple speakers. It outperforms the original Whisper model in terms of transcription speed and timestamp accuracy, making it well-suited for use cases such as video captioning, podcast transcription, and meeting notes generation.

What can I use it for?

whisperx can be used in a variety of applications that require accurate speech-to-text conversion, such as:

  • Video Captioning: Generate captions for videos with precise timing and speaker identification.
  • Podcast Transcription: Automatically transcribe podcasts and audio recordings with timestamps and diarization.
  • Meeting Notes: Transcribe meetings and discussions, with the ability to attribute statements to individual speakers.
  • Voice Interfaces: Integrate whisperx into voice-based applications and services for improved accuracy and responsiveness.

Things to try

Consider experimenting with different model variants of whisperx to find the best fit for your hardware and use case. The victor-upmeet/whisperx model is a good starting point, but the victor-upmeet/whisperx-a40-large and victor-upmeet/whisperx-a100-80gb models may be more suitable if you encounter memory issues when dealing with long audio files or when performing alignment and diarization.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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