TTS_haryanvi_bangru_vits_based_model

---

language:

• haryanvi(bangru) tags:
• text-to-speech
• TTS
• generative-ai
• speech
• low-resource-language
• haryanvi license: apache-2.0 datasets:
• Satyam-Srivastava/RDS metrics:
• mos
• wer pipeline_tag: text-to-speech

---

🎤 Haryanvi Text-to-Speech (TTS) Model

This model converts Haryanvi text into natural-sounding speech.

It is designed to support low-resource Indian dialects, focusing on:

• Native pronunciation
• Regional tone
• Real-world usability (education, voice assistants)

⚡ Built as part of Data Science & AI Lab Project.

🚀 Motivation

Most TTS systems do not support regional dialects like Haryanvi.

This project aims to:

• Preserve regional language identity
• Enable voice-based learning tools
• Build inclusive AI for Indian users

💡 Unlike generic Hindi TTS, this model captures Haryanvi phonetics and accent patterns.

🧠 Model Details

• Architecture: VITS
• Vocoder: HiFi-GAN
• Framework: PyTorch
• Task: Text-to-Speech (TTS)

Input

• Haryanvi text

Output

• Speech waveform (.wav)

📊 Dataset

• Satyam-Srivastava/RDS(audio_data is copied from ankit_dhiman_you can see in card as well. For audio data credit goes to Ankitdhiman.)
• Total Samples: 5515
• Duration: approx 1 hours
• Format: WAV files

Preprocessing

• Noise removal
• Normalization
• Text cleaning (Hindi → Haryanvi phonetics)

⚙️ Training

• Epochs: 100
• Batch Size: 32
• Optimizer: ---
• Learning Rate: 1e-5

Hardware

• GPU: (T4 / A100 )

Training Strategy

• Fine-tuning on low-resource data
• Augmentation for robustness

📈 Evaluation

Metrics

• MOS (Mean Opinion Score): X.X
• WER (Word Error Rate): X%

Observations

• Good pronunciation for common phrases
• Slight errors in rare words

🎧 Sample Outputs

⚠️ Limitations

• Limited dataset size

🔮 Future Improvements

• Multi-speaker Haryanvi TTS
• Emotion-aware speech generation
• Integration with RAG-based learning platform

🧪 Usage

from transformers import pipeline

tts = pipeline("text-to-speech", model="your-username/model-name")

output = tts("राम राम भाई")

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👨‍💻 12. Contributors

## 👨‍💻 Contributors

- Satyam – Documentation & Model run 
- Abhishek – Text Processing 
- Fazlur – Audio Pipeline
- Sanket – Deployment & HuggingFace


## ❤️ Acknowledgements

Thanks to:
- Hugging Face
- Open-source TTS community
- Course instructors & TAs

## 🌍 Impact

This project contributes to:
- Digital inclusion of rural dialects
- Voice-based education systems
- Preservation of regional languages