Analyzed Argentina’s Ecosystem and Developed Speech Processing Pipeline
- Day: 2025-08-04
- Time: 12:50 to 13:10
- Project: Business
- Workspace: WP 1: Strategic / Growth & Development
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Argentina, Ecosystem, RTTM, Speech Processing, Python
Description
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.
Evidence
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