Enhanced Whisper Transcription and Diarization
- Day: 2025-08-04
- Time: 13:30 to 14:20
- Project: Dev
- Workspace: WP 2: Operational
- Status: In Progress
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Whisper, Transcription, Audio Processing, Diarization, Automation
Description
Session Goal
The session aimed to improve transcription quality and diarization using the Whisper model, focusing on Spanish audio and optimizing the transcription pipeline.
Key Activities
- Updated the Whisper transcription cell to disable timestamp post-processing and avoid slice-index errors.
- Assessed transcription quality issues in Spanish audio, recommending a switch to a multilingual model for better accuracy.
- Explored leveraging diarization for automatic speech recognition (ASR) to enhance transcription segmentation.
- Conducted a quality assessment of transcription outputs, comparing diarization-driven small-model runs against web app outputs.
- Outlined an end-to-end architecture for audio/video processing, converting content into AI-curated Markdown pages.
- Developed a robust ingestion pipeline for daily content harvesting, including subscription management and a daily scheduler.
Achievements
- Successfully updated the Whisper transcription settings to improve segment output.
- Identified and recommended solutions for transcription quality issues in Spanish audio.
- Established a scalable architecture for audio/video content processing.
Pending Tasks
- Implement the recommended switch to a multilingual model for Spanish audio transcription.
- Finalize the ingestion pipeline for daily content harvesting, ensuring seamless integration with existing systems.
Evidence
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- event_ids: []