https://github.com/kr1shnasomani/tonesense

Speech emotion recognition from audio clips using CNN
https://github.com/kr1shnasomani/tonesense

deep-learning keras librosa matplotlib neural-network numpy pandas scikit-learn tensorflow

Last synced: 2 months ago
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Speech emotion recognition from audio clips using CNN

• Host: GitHub
• URL: https://github.com/kr1shnasomani/tonesense
• Owner: kr1shnasomani
• Created: 2024-12-10T18:53:55.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-30T12:04:31.000Z (over 1 year ago)
• Last Synced: 2025-04-06T13:19:01.987Z (about 1 year ago)
• Topics: deep-learning, keras, librosa, matplotlib, neural-network, numpy, pandas, scikit-learn, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 1.53 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
ToneSense



  



The project leverages Librosa for audio feature extraction, including MFCCs and spectral features and uses TensorFlow to develop a deep learning model for classifying emotions like happiness, sadness and anger. It incorporates spectrogram analysis for visual insights and supports real-time emotion recognition for practical applications.


## Execution Guide:

1. Clone the repository:

   ```

   git clone https://github.com/kr1shnasomani/ToneSense.git

   cd ToneSense

   ```

2. Download the dependencies:

   ```

   pip install -r requirements

   ```

3. Run the code and it will save the model with the name `model.keras`

## Accuracy & Loss Over Epochs:

![image](https://github.com/user-attachments/assets/e338a8ab-2a28-48ed-869a-ef683602cbc5)

![image](https://github.com/user-attachments/assets/95158724-54a8-4734-a009-72510c038877)

## Model Prediction:

   Input (the file is in `.mp4` format as GitHub doesn't support audio files):

   

   https://github.com/user-attachments/assets/d74d7fdf-802e-4742-8cde-9e434c969e32

   Output:

   

   ![image](https://github.com/user-attachments/assets/1609e53a-ac10-46f6-8ddd-c413baddc4d1)