Audio Retrieval System

This MATLAB code for Chinese audio retrieval was developed during my first year of graduate studies, designed to assist researchers and developers in practical applications. The system implements audio fingerprinting and content-based retrieval algorithms that can identify and retrieve audio files with high accuracy. Key features include feature extraction using MFCC (Mel-Frequency Cepstral Coefficients), audio fingerprint generation through spectral analysis, and similarity matching algorithms for efficient retrieval. The code structure incorporates robust error handling and supports various audio formats through MATLAB's audio processing toolbox. Implementation includes preprocessing stages for noise reduction and normalization, followed by feature vector computation and database indexing. The retrieval mechanism uses distance metrics like Euclidean or cosine similarity for matching audio samples. Whether you're conducting audio data analysis or pursuing related research, this codebase provides a solid foundation with comprehensive functionality. During development, I considered various operational scenarios and optimized the code for clarity and ease of use, ensuring straightforward integration into existing projects. The modular design allows for customization of individual components such as feature extraction methods or matching algorithms. Should you encounter any issues or require further implementation guidance, please feel free to reach out for technical support and detailed documentation.