Project goal: provide a front-end/UI that enables full workflows for transcribing audio using Whisper
Background: OpenAI recently released Whisper, which achieves close to human-level transcription, far better than existing solutions like Otter and Zoom's built-in transcription. Unfortunately, Whisper does not provide any UI for editing transcripts, labeling speakers, or correcting errors.
Project MVP and stages:
- MVP: UI supports importing .vtt produced by Whisper, playing audio for segments of the transcription, combining transcript segments, and labeling segments. Once edited, the transcript can be exported in a usable format.
- Future goal: Provide user-friendly UI that enables downloading and setting up Whisper backend
- Future goal: Support running Whisper transcription from within the app
- Future goal: Integrate with ffmpeg and youtube-dl to make it easy to transcribe youtube videos and recordings not already in .wav format.
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