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metadata

title: Hindi Speech Emotion & Recommendation System
emoji: 🎭
colorFrom: red
colorTo: pink
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit

🎭 Hindi Speech Emotion & Action Recommendation System

An AI-powered pipeline for Hindi/Hinglish emotion analysis and contextual action recommendations.

🧩 System Pipeline

🎙️ Audio Input (Hindi/Hinglish) →
📝 Indic Conformer 600M ASR →
🎭 XLM-RoBERTa Emotion Detection (13 emotions) →
💭 Hindi Sentiment Analysis →
🤖 Llama 3.1 8B Recommendation Generation →
✅ Validation & Helpline Integration →
💬 Personalized Hindi Recommendation

✨ Features

🎙️ Advanced ASR — Indic Conformer 600M for accurate Hindi/Hinglish transcription
🎭 13 Emotions — joy, happiness, sadness, anger, fear, distress, panic, love, surprise, calm, neutral, excitement, frustration
💭 Sentiment Analysis — Positive/Neutral/Negative with confidence scores
🤖 AI Recommendations — Context-aware suggestions powered by Llama 3.1 8B
🚨 Crisis Detection — 100+ emergency keywords in Hindi/English
🧠 Mental Health Support — Specialized detection for depression, anxiety, isolation
💔 Grief & Relationship — Targeted support for loss and relationship distress
✅ Automatic Validation — Ensures helplines are included when needed

⚙️ Configuration

Set the following environment variable in Space Settings → Variables:

Variable	Description
`HF_TOKEN`	Your Hugging Face token (required for Llama 3.1 access)

Get token from: https://huggingface.co/settings/tokens
Accept Llama 3.1 license here: meta-llama/Llama-3.1-8B-Instruct

🆘 Emergency Helplines (India)

Service	Number	Availability
🚨 Police / Emergency	112	24/7
👩 Women’s Helpline	181	24/7
🆘 Women in Distress	1091	24/7
🧠 Vandrevala Foundation	9152987821	24/7
🏥 NIMHANS Mental Health	08046110007	24/7
💙 AASRA Suicide Prevention	9820466726	24/7

🧠 Models Used

Task	Model
ASR	ai4bharat/indic-conformer-600m-multilingual
Sentiment	LondonStory/txlm-roberta-hindi-sentiment
Emotion	joeddav/xlm-roberta-large-xnli
LLM	meta-llama/Llama-3.1-8B-Instruct

🔒 Privacy & Safety

✅ No permanent data storage
✅ All processing in-memory
✅ Automatic helpline integration
✅ Crisis prioritization
✅ Privacy-first architecture