Hey there! Welcome to my Deep Learning Sound Classification Project. This project focuses on using deep learning techniques to classify sounds. I've started with a simple test project where I downloaded 5 episodes each from three anime series: Sword Art Online, Dr. Stone, and Jujutsu Kaisen. I converted the sound clips into 5-second segments and performed normalization to prepare the data for classification.
In this test project, I have used a small dataset with sounds from the anime series mentioned above. However, I'd like to mention that this is just a starting point and that the model performs better on datasets containing a wider variety of sounds, especially human voices and environmental sounds.
Wondering how you can get started with this project? It's quite simple! Here are the steps:
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Install Required Libraries: Make sure you have all the necessary libraries installed (such as PyTorch, librosa, numpy, etc.).
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Download the Sound Data: If you're interested in running the test project, you can download the sound data from Sword Art Online, Dr. Stone, and Jujutsu Kaisen anime series. Alternatively, you can use your own sound data for classification.
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Preprocess the Data: Preprocess the sound clips, segment them into 5-second pieces, and perform normalization to make the data suitable for training the deep learning model.
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Train the Model: Train your deep learning model using the preprocessed sound data.
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Analyze the Results: Evaluate the model's accuracy, performance, and reliability on the test dataset.
I'm really excited about this project and I would love to make it better. If you have any ideas for improvements, new features, or if you find any issues, please don't hesitate to let me know. Contributions are more than welcome, and I truly appreciate any help in enriching this project further.
This project is open-source and licensed under the MIT License. For more details, please see the "LICENSE" file.
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