Developed Python Scripts for Audio Diarization and Transcription

2 min read

📅 2025-08-05 — Session: Developed Python Scripts for Audio Diarization and Transcription

🕒 01:45–02:50
🏷️ Labels: Python, Diarization, RTTM, Whisper, Pyannote
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to develop and refine Python scripts for audio diarization and transcription, focusing on generating and utilizing RTTM files for speaker identification.

Key Activities

  • Implemented a Python script using the Whisper model to process audio files in formats such as .wav, .m4a, and .webm, converting them to .wav for diarization and transcription.
  • Developed a script to generate RTTM files using the pyannote.audio library, processing .wav files and saving the output to a specified directory.
  • Updated scripts to handle errors, such as checking if the pipeline is None and aborting with a clear message to prevent processing errors.
  • Provided guidance on troubleshooting issues related to missing RTTM files, ensuring correct execution paths.
  • Integrated commands for cleaning caches on Linux systems to recover disk space, aiding in maintaining system performance.

Achievements

  • Successfully created scripts for diarization and transcription, generating outputs in JSON and TXT formats with speaker labels and timestamps.
  • Enhanced error handling in RTTM generation scripts to improve reliability.

Pending Tasks

  • Further testing and validation of the scripts in diverse audio processing scenarios to ensure robustness.
  • Exploration of additional optimization techniques for faster processing.

Graph View

Backlinks