README.md

---
title: AInterviewer SER Analyzer
emoji: 🎙️
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
pinned: false
---

# AInterviewer SER Analyzer

Speech Emotion Recognition (SER) inference Space for the AInterviewer project.

## Endpoints

- `GET /health` — Returns `{"status": "ok", "svm_loaded": bool}`
- `GET /version` — Returns `{"version": "ser_colombian_v1"}` when SVM loaded, `"emotion2vec_plus_base"` in fallback mode
- `POST /analyze` — Accepts WAV file, returns `{"dominant": str, "distribution": {...}, "model": str}`

## Architecture

Two-stage inference:
1. emotion2vec_plus_large extracts 768-dim audio embeddings
2. SVM Pipeline (StandardScaler + SVC) classifies into 4 emotions: angry, happy, neutral, sad

Falls back to emotion2vec+ direct classification if the Colombian SVM artifact is unavailable.
That fallback is an operational safety net, not the final Colombian model deployment.