Comprehensive MATLAB Source Code for Speech Signal Feature Extraction
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Resource Overview
A complete MATLAB implementation for speech signal feature extraction, including PLP feature extraction, MFCC feature extraction, LPCC feature extraction, and RASTA transformation with detailed algorithmic implementations and feature parameter configurations.
Detailed Documentation
This repository provides a comprehensive MATLAB source code package for speech signal feature extraction. The implementation includes multiple feature extraction methodologies: Perceptual Linear Predictive (PLP) coefficients, Mel-Frequency Cepstral Coefficients (MFCC), Linear Predictive Cepstral Coefficients (LPCC), and RASTA (Relative Spectral) filtering transformation. Each module is implemented with proper framing, windowing, and spectral processing techniques, ensuring robust feature extraction for speech processing applications. The code structure follows modular design principles, allowing easy integration of individual feature extraction components while maintaining configurable parameters for frame size, overlap, and filter bank specifications.
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