This project is aimed at analyzing zebra finch audio data, preprocessing the data, and developing a machine learning model to detect and categorize the different calls of zebra finches. The main steps involved in this project are:
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Data Collection: The audio data for zebra finches is collected and stored in a database.
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Data Preprocessing: Random samples of audio data are selected and concatenated to create artificial data. This data is then labeled with the help of available labeling systems.
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Machine Learning Model: A machine learning algorithm is implemented to detect syllables in zebra finch calls and classify them into relevant categories.
- Data Preprocessing:
Run the Jupyter Notebook data_preprocessing.ipynb to create artificial data and apply labels to the zebra finch calls.
- Machine Learning Model:
Run the Jupyter Notebook zebra_finch_classification.ipynb to train and evaluate the machine learning model for call detection and * categorization.
- Additional Notes:
Add any additional notes or instructions specific to your project.
If you would like to contribute to this project, please follow these steps:
Fork the repository.
Create a new branch for your feature or bug fix: git checkout -b feature-name
Make your changes and commit them: git commit -m 'Description of changes'
Push your changes to your fork: git push origin feature-name
Create a pull request to merge your changes into the main repository.
Tahoura Morovati: t.morovati.99@gmail.com
Feel free to customize this README file with additional information and details specific to your project. Good luck with your zebra finch audio analysis project!