Developed and Optimized YouTube Audio Diarization Script

• Day: 2025-08-05
• Time: 00:10 to 00:50
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Diarization, Youtube, Automation, Error Handling

Description

Session Goal: The primary objective of this session was to develop and optimize a Python script for diarizing audio from YouTube videos, utilizing the pyannote.audio library.

Key Activities:

• Developed a Python script to download audio from YouTube, convert it to WAV format, and perform speaker diarization using the pyannote.audio library.
• Refined the script to handle YouTube URLs effectively and resolve parameter errors.
• Automated the diarization process by creating a two-part workflow: generating a text file of YouTube URLs from a DataFrame and executing the diarization script with correct arguments.
• Addressed SystemExit: 2 errors in Jupyter Notebook by providing solutions for executing the script from the command line or adapting argument parsing.
• Provided methods for correctly reading JSON Lines files in Pandas to avoid data handling errors.

Achievements:

• Successfully developed and refined a functional diarization script for YouTube audio.
• Automated the diarization process, enhancing efficiency and accuracy.
• Resolved key errors and improved script robustness.

Pending Tasks:

• Further testing of the script in diverse environments to ensure compatibility and performance.

Evidence

• source_file=2025-08-05.sessions.jsonl, line_number=2, event_count=0, session_id=019b9141f3c74d70ea9b5baff27ee75da69d123741de64037b1b780f84ec5ee7
• event_ids: []