End-to-end speech processing concept for automatic speech recognition, word-level timestamps, and speaker diarization.
audioX is planned as an audio intelligence pipeline that can turn conversations into structured transcripts with speaker labels and timing metadata. The goal is to combine ASR, diarization, and transcript post-processing into one workflow for interviews, meetings, calls, and long-form recordings.
- Speech-to-text transcription.
- Word-level timestamp extraction.
- Speaker diarization for multi-speaker audio.
- Clean transcript export for downstream search, summaries, and analytics.
- Modular pipeline design so ASR and diarization backends can be swapped.
- Python
- ASR model integration
- Speaker diarization model integration
- Audio preprocessing
- Transcript post-processing
This repository is currently a public project placeholder. The next step is to add the pipeline implementation, sample commands, and evaluation notes.
- Add audio preprocessing utilities.
- Add ASR inference script.
- Add diarization stage.
- Merge ASR words with speaker turns.
- Export transcript JSON and readable text.