📅 2025-08-04 — Session: Analyzed Argentina’s Ecosystem and Developed Speech Processing Pipeline
🕒 12:50–13:10
🏷️ Labels: Argentina, Ecosystem, RTTM, Speech Processing, Python
📂 Project: Business
Session Goal
The session aimed to explore the existing ecosystem in Argentina, focusing on identifying potential opportunities and gaps in archival and discourse platforms. Additionally, it aimed to develop a comprehensive speech processing pipeline using RTTM files.
Key Activities
- Conducted research on Argentina’s ecosystem, focusing on watchdogs and think tanks to identify potential competitors and collaborators.
- Analyzed the landscape of archival and discourse platforms in Argentina, identifying opportunities for new initiatives.
- Developed Python scripts to read RTTM files, handle file paths, and process data for speaker diarization.
- Created a workflow for integrating RTTM diarization with ASR results to produce labeled transcripts.
- Implemented a Jupyter notebook to facilitate the transcription and diarization alignment pipeline, using the Faster Whisper model.
Achievements
- Identified key players and gaps in the Argentinian market that could influence new business strategies.
- Successfully developed and tested a speech processing pipeline that integrates diarization and ASR for audio analysis.
- Created reusable Python code and Jupyter notebooks for ongoing and future projects.
Pending Tasks
- Further validation and testing of the diarization and ASR integration process to ensure accuracy and reliability.
- Exploration of additional data tools and archival completeness in Argentina’s ecosystem.