EchoQuest
Challenge
Extracting key insights from hours of recorded interviews is a manual and time-consuming task.
Solution
I designed 'EchoQuest,' an end-to-end pipeline that processes raw audio into a searchable knowledge base. It enhances audio, separates speakers (diarization), transcribes with OpenAI's Whisper, and indexes the content.
Result
A powerful analysis tool where a user can ask natural language questions about the interview ('What did Sarah say about the budget?') and get instant, accurate answers.
Key Highlights
Audio Enhancement
Improves audio quality for better transcription.
Speaker Recognition
Identifies who's speaking throughout the recording.
AI-Powered Analysis
Ask natural questions about interview content.

Technology Stack
Audio
PyTorch Audio
Whisper
Pyannote
Analysis
LangChain
Transformers
Infra
FastAPI
Redis
PostgreSQL