MATLAB Program for Speech Frame Segmentation

In speech signal processing, MATLAB can be used to develop programs for speech frame segmentation. Speech frame segmentation involves dividing speech signals into short-time segments, enabling further analysis and processing of each segment. MATLAB provides robust functionality for implementing speech frame segmentation through its rich signal processing toolbox and function libraries, offering greater possibilities and flexibility in speech signal processing. A typical MATLAB implementation involves key functions and algorithms such as: - Using `audioread()` to load speech signals with proper sampling rate considerations - Implementing overlap-add methods with functions like `buffer()` for creating overlapping frames - Calculating optimal frame size (typically 20-30ms) and overlap percentage (commonly 50%) using windowing techniques - Applying window functions such as Hamming window via `hamming()` to reduce spectral leakage - Utilizing matrix operations for efficient batch processing of speech frames The benefits of using MATLAB for speech frame segmentation include access to built-in functions for spectral analysis, feature extraction, and real-time processing capabilities. This approach facilitates better understanding and manipulation of speech signals through systematic frame-based analysis, making MATLAB an excellent choice for speech processing applications requiring precise temporal segmentation and spectral characterization.