audio-transcribe

Transcribe audio with word-level timestamps by running the transcribe.py script, which uses WhisperX to convert speech into text and optionally applies alignment to produce precise timing data for your media files.

Yes, you can generate SRT and VTT subtitles from video files by running the transcription process, which outputs timed text formats suitable for video captions and podcast transcripts.

WhisperX supports multilingual speech recognition, allowing you to transcribe audio from meetings and podcasts into text with word-level timestamps across different languages.

The best way to convert speech to text for archival keyword search is using WhisperX to output a JSON or TXT transcript, providing accurate word-level timing data to index and retrieve audio content.

Yes, you need Python 3.12 along with the WhisperX dependency to transcribe video files into JSON format, ensuring the transcription script runs correctly and produces accurate text alignment.

Word-level alignment for meeting minutes transcription works by applying WhisperX models to map individual text tokens to precise audio timestamps, resulting in highly accurate and searchable text outputs.