EchoQuest

Interview Analysis System

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.

Visualization of EchoQuest's audio processing and analysis workflow.

Technology Stack

Audio
PyTorch Audio
Whisper
Pyannote
Analysis
LangChain
Transformers
Infra
FastAPI
Redis
PostgreSQL
EchoQuest | Fanktank