MATLAB Toolbox Source Code for Speech Signal Processing

In this article, we introduce how to utilize MATLAB toolboxes for processing speech signals. We explore fundamental concepts of speech signal processing, such as signal sampling and quantization, along with practical MATLAB implementation methods using built-in functions like audioread for signal acquisition and resample for rate conversion. Furthermore, we delve into advanced topics including speech recognition using hidden Markov models (HMM) with the trainHMM function and speech synthesis through concatenative methods or formant synthesis employing the synthesize toolbox, providing corresponding MATLAB code examples for reference. Finally, we discuss practical applications of speech signal processing technologies, such as implementing voice recognition in intelligent assistants using pattern matching algorithms and speech synthesis in autonomous vehicles through text-to-speech (TTS) systems with prosody control. Thus, this article not only supplies MATLAB toolbox source code but also delivers comprehensive knowledge and application guidelines with high reference value, featuring code segments demonstrating frame-based processing, mel-frequency cepstral coefficients (MFCC) extraction, and real-time implementation techniques.