{"id":15180595,"url":"https://github.com/Mike014/Audio-Classification","last_synced_at":"2025-10-26T19:31:56.613Z","repository":{"id":255515119,"uuid":"852320452","full_name":"Mike014/Audio-Classification-","owner":"Mike014","description":"This is a prototype Django application that allows users to upload audio files and classify them using machine learning techniques.","archived":false,"fork":false,"pushed_at":"2024-09-04T15:59:01.000Z","size":7796,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-10-11T07:05:15.985Z","etag":null,"topics":["ai","audio","django","django-application","machine-learning","mfcc","pca","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Mike014.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-04T15:52:24.000Z","updated_at":"2024-09-04T16:00:05.000Z","dependencies_parsed_at":"2024-09-05T22:13:29.036Z","dependency_job_id":"4a34e25a-c6f7-4dff-9cf7-cb1f9e99508b","html_url":"https://github.com/Mike014/Audio-Classification-","commit_stats":null,"previous_names":["mike014/audio-classification-"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mike014%2FAudio-Classification-","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mike014%2FAudio-Classification-/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mike014%2FAudio-Classification-/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Mike014%2FAudio-Classification-/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Mike014","download_url":"https://codeload.github.com/Mike014/Audio-Classification-/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":219862256,"owners_count":16555957,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","audio","django","django-application","machine-learning","mfcc","pca","python"],"created_at":"2024-09-27T16:23:14.486Z","updated_at":"2025-10-26T19:31:52.665Z","avatar_url":"https://github.com/Mike014.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Audio Classification App\n\n## Overview\n\nThis is a prototype Django application that allows users to upload audio files and classify them using machine learning techniques. The app uses Principal Component Analysis (PCA) for feature reduction and K-Nearest Neighbors (KNN) for classification. The application is designed to be extendable, allowing for the addition of more data and classes in the future.\n\n## Features\n\n- **Upload Audio Files**: Users can upload audio files through a web interface.\n- **Feature Extraction**: Extracts Mel-Frequency Cepstral Coefficients (MFCC) from the audio files.\n- **Dimensionality Reduction**: Uses PCA to reduce the dimensionality of the extracted features.\n- **Classification**: Classifies the audio files using a pre-trained KNN model.\n- **Results Display**: Shows the predicted class of the uploaded audio file.\n\n## Installation\n\n1. **Clone the Repository**:\n\n```bash\ngit clone https://github.com/yourusername/audio_classification.git\ncd audio_classification\n```\n\n2. **Create a Virtual Environment**:\n\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Windows use `venv\\Scripts\\activate`\n```\n\n3. **Install Dependencies**:\n\n```bash\npip install -r requirements.txt\n```  \n\n4. **Run Migrations**:\n\n```bash\npython manage.py migrate\n```\n\n5. **Start the Development Server**:\n\n```bash\npython manage.py runserver\n```\n\n\n6. **Access the Application**:\n    Open your web browser and go to `http://127.0.0.1:8000/`.\n\n## Usage\n\n1. **Upload an Audio File**:\n    - Navigate to the upload page.\n    - Select an audio file and click the \"Upload\" button.\n\n2. **View Classification Results**:\n    - After uploading, you will be redirected to a results page showing the predicted class of the audio file.\n\n## Concepts\n\n### Feature Extraction\n\nThe application uses the `librosa` library to extract MFCC features from the audio files. MFCCs are commonly used in audio processing to represent the short-term power spectrum of a sound.\n\n### Dimensionality Reduction\n\nPCA is used to reduce the dimensionality of the extracted features. This helps in reducing noise and simplifying the data for classification.\n\n### Classification\n\nA pre-trained KNN model is used to classify the audio files. KNN is a simple, yet effective, classification algorithm that assigns a class based on the majority class of the nearest neighbors.\n\n## Extending the Application\n\nThis application is a prototype and can be extended in several ways:\n\n- **Add More Data**: Collect and label more audio files to improve the accuracy of the model.\n- **Extract Additional Features**: Use other audio features like chroma, spectral contrast, etc.\n- **Use Advanced Models**: Experiment with more complex models like Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN).\n\n## Screenshots\n\n### Upload Page\n![Upload Page](screenshot/Cattura.PNG)\n\n### Results Page\n![Results Page](screenshot/Cattura%201.PNG)\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Acknowledgements\n\n- [librosa](https://librosa.org/) for audio processing.\n- [scikit-learn](https://scikit-learn.org/) for machine learning algorithms.\n- [Django](https://www.djangoproject.com/) for the web framework.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMike014%2FAudio-Classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FMike014%2FAudio-Classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMike014%2FAudio-Classification/lists"}