MATLAB Code Implementation for Speech Feature Extraction

Speech feature extraction is an audio data processing method that analyzes audio signals by calculating metrics such as zero-crossing rate, energy ratio, and short-term energy. Before performing speech feature extraction, MAV audio files must be imported as input data. Key implementation aspects in MATLAB include: - Using `audioread()` function to import MAV audio files and obtain waveform data and sampling rate - Calculating zero-crossing rate by detecting signal sign changes across consecutive samples - Computing short-term energy using frame-based analysis with overlapping windows - Deriving energy ratio metrics by comparing signal energy across different frequency bands - Implementing frame segmentation with typical window sizes of 20-30ms and 50% overlap - Utilizing MATLAB's signal processing toolbox functions for efficient feature computation The algorithm typically involves preprocessing steps like framing, windowing, and normalization before feature calculation to ensure robust performance across different audio conditions.