https://github.com/palak-463/tablataalrecognitionsystem

Software built using Python which makes use of CNN and FNN to detect the Taals of the Tabla, an Indian classical music instrument. 🎛️
https://github.com/palak-463/tablataalrecognitionsystem

cnn deep-learning flask fnn librosa numpy os pickle python scikit-learn

Last synced: about 1 month ago
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Software built using Python which makes use of CNN and FNN to detect the Taals of the Tabla, an Indian classical music instrument. 🎛️

• Host: GitHub
• URL: https://github.com/palak-463/tablataalrecognitionsystem
• Owner: palak-463
• Created: 2023-12-27T15:08:36.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-09-14T09:54:54.000Z (5 months ago)
• Last Synced: 2024-11-11T11:47:09.788Z (3 months ago)
• Topics: cnn, deep-learning, flask, fnn, librosa, numpy, os, pickle, python, scikit-learn
• Language: Python
• Homepage:
• Size: 3.6 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 🥁 Tabla Taal Recognition System

The **Tabla Taal Recognition System** is an advanced research project focusing on the recognition and classification of Classical Indian Music **Tabla Taals**. The system identifies renowned Taals like **Addhatrital, Ektal, Rupak, Dadra, Deepchandi, Jhaptal, Trital,** and **Bhajani**. By using machine learning models, including **Feedforward Neural Networks (FNN)** and **Convolutional Neural Networks (CNN)**, the system effectively analyzes and categorizes complex rhythmic patterns in Indian Classical Music. 




## 🎯 System Overview

This system uses a **Graphical User Interface (GUI)** where users can upload audio files containing Tabla performances. Once uploaded, the system processes the audio, recognizes the Taal, and displays the classification result.




## 🔑 Working

- **Taal Recognition**: Efficient recognition of various classical **Tabla Taals**.

- **Machine Learning Models**: Uses **FNN** and **CNN** for high-accuracy Taal classification.

- **GUI for Easy Interaction**: Provides a simple and user-friendly interface for uploading and analyzing audio files.

- **Dataset Training**: Trained on a large set of Classical Indian Music recordings for robust and accurate results.




## 📋 System Flow

1. **User Input**: The user uploads an audio file through the **GUI**.

2. **Audio Processing**: The audio file is processed to extract relevant features.

3. **Model Prediction**:

   - **FNN and CNN** models are used to predict the Taal.

4. **Result Display**: The system displays the recognized Taal on the interface.




## ✨ Technologies Used

| Frontend and Backend | 

|----------------------|

| **Python**           | 




## 🚀 Features

- 🥁 **Taal Classification**: Categorizes various Classical Indian Music Tabla Taals.

- 📊 **FNN & CNN**: Utilizes state-of-the-art **Feedforward** and **Convolutional Neural Networks** for analysis.

- 🎛️ **User-Friendly Interface**: Simple interface for uploading audio files and viewing results.

- 📈 **Accurate Results**: Highly accurate recognition through a trained model on Indian Classical Music data.