PROJECT_SUMMARY.md

# Speech Recognition Dataset - Project Summary

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Speech Recognition Dataset - Project Summary
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Project: Speech Recognition Dataset
Description: Audio speech recognition dataset with labeled speech samples
for training speech-to-text and voice recognition models.

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DEVELOPER INFORMATION
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Website: https://rskworld.in
Founded by: Molla Samser
Designer & Tester: Rima Khatun
Email: help@rskworld.in
Support: support@rskworld.in
Phone: +91 93305 39277
Address: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147

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COPYRIGHT NOTICE
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© 2026 RSK World. All rights reserved.
This dataset is provided for educational and research purposes.

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-->

## Project Overview

This is a complete Speech Recognition Dataset project with:
- Interactive demo page (HTML/CSS/JavaScript)
- Python scripts for data processing and model training
- Jupyter notebook for data exploration
- Complete documentation

## Project Structure

```
speech-recognition/
├── index.html # Main demo page
├── README.md # Project documentation
├── LICENSE # License information
├── requirements.txt # Python dependencies
├── .gitignore # Git ignore rules
├── PROJECT_SUMMARY.md # This file
│
├── css/
│ └── style.css # Stylesheet with developer info
│
├── js/
│ └── script.js # JavaScript with developer info
│
├── data/
│ ├── audio/ # Audio files directory
│ │ └── README.txt # Instructions
│ ├── features/ # Extracted features directory
│ │ └── README.txt # Instructions
│ ├── metadata.csv # Dataset metadata
│ └── transcripts.json # Text transcripts
│
├── scripts/
│ ├── load_dataset.py # Dataset loader
│ ├── preprocess.py # Feature extraction
│ ├── train_model.py # Model training
│ └── example_usage.py # Usage examples
│
├── notebooks/
│ └── exploration.ipynb # Data exploration notebook
│
└── models/ # Trained models directory
```

## Files Created

### Frontend Files
1. **index.html** - Interactive demo page with:
- Hero section with statistics
- Features showcase
- Audio samples player
- Statistics and charts
- Code examples
- Download section

2. **css/style.css** - Complete stylesheet with:
- Dark theme design
- Responsive layout
- Animations and transitions
- Developer information in comments

3. **js/script.js** - JavaScript functionality:
- Mobile menu toggle
- Smooth scrolling
- Counter animations
- Waveform visualization
- Audio player controls
- Chart.js integration
- Developer information in comments

### Python Scripts
1. **scripts/load_dataset.py** - Dataset loader class with methods to:
- Load metadata and transcripts
- Get audio files by ID
- Filter by speaker or category
- Get dataset statistics

2. **scripts/preprocess.py** - Feature extraction with:
- MFCC extraction
- Mel spectrogram extraction
- Chroma features
- Spectral contrast
- Batch processing

3. **scripts/train_model.py** - Model training with:
- LSTM/Bidirectional LSTM architecture
- Sequence padding
- Train/validation/test split
- Model checkpointing
- Evaluation metrics

4. **scripts/example_usage.py** - Usage examples demonstrating:
- Loading dataset
- Preprocessing
- Feature extraction
- Model training

### Data Files
1. **data/metadata.csv** - Sample metadata with columns:
- id, file_name, speaker, duration, transcript, category

2. **data/transcripts.json** - JSON mapping of file IDs to transcripts

### Documentation
1. **README.md** - Complete project documentation
2. **LICENSE** - License information
3. **requirements.txt** - Python dependencies
4. **.gitignore** - Git ignore rules

### Notebooks
1. **notebooks/exploration.ipynb** - Jupyter notebook for:
- Data loading
- Statistical analysis
- Visualizations
- Audio feature extraction
- Transcript analysis

## Developer Information

All files include developer information in comments:
- **Website**: https://rskworld.in
- **Founded by**: Molla Samser
- **Designer & Tester**: Rima Khatun
- **Email**: help@rskworld.in
- **Support**: support@rskworld.in
- **Phone**: +91 93305 39277
- **Address**: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147

## Features Implemented

✅ Interactive demo page with modern UI
✅ Audio waveform visualizations
✅ Statistics and charts
✅ Code examples for Python, Librosa, and TensorFlow
✅ Complete Python API for dataset loading
✅ Feature extraction pipeline
✅ Model training scripts
✅ Jupyter notebook for exploration
✅ Complete documentation
✅ Developer information in all files

## Next Steps

1. Add actual audio files to `data/audio/` directory
2. Update `metadata.csv` with complete dataset information
3. Run preprocessing: `python scripts/preprocess.py`
4. Train model: `python scripts/train_model.py`
5. Explore data: Open `notebooks/exploration.ipynb`

## Contact

For questions or support:
- **Email**: help@rskworld.in
- **Support**: support@rskworld.in
- **Phone**: +91 93305 39277
- **Website**: https://rskworld.in

---

© 2026 RSK World. All rights reserved.