Explore MATLAB source code curated for "语音识别" with clean implementations, documentation, and examples.
Implementation of LPCC (Linear Predictive Cepstral Coefficients) as a speech feature extraction method for speech recognition systems developed using MATLAB, including algorithmic steps and signal processing techniques.
Speech Recognition (commonly abbreviated) refers to the translation of spoken words into text. It is also known as "Automatic Speech Recognition (ASR)", "Computer Speech Recognition", or "Speech-to-Text (STT)". The technology finds applications in voice-activated routing for customer call center systems, voice-dialing mobile phones, and numerous other daily applications. Robust speech recognition systems combine the ability to identify speech with capabilities to filter out noise and adapt to varying acoustic conditions, such as differences in speaking speed and accents.
Implementation of isolated word speech recognition using Hidden Markov Model (HMM) through MATLAB programming
Time-frequency analysis of speech signals is a crucial area of research. Speech recognition technology, as one of the key technologies driving the development of intelligent and automated information societies, holds significant research importance and practical value. Through nearly five decades of intensive exploration and research, speech recognition technology has achieved remarkable progress, with some mature techniques already being applied in daily life. However, overall, speech recognition still presents considerable challenges in both research and practical applications. This article provides a comprehensive overview of speech recognition technology, covering key techniques, specific applications, and current difficulties, and includes MATLAB-based simulation analysis of individual speech samples. Code implementations focus on signal processing techniques such as Short-Time Fourier Transform (STFT) and wavelet analysis for feature extraction.
Classic MATLAB code implementations for speech recognition, featuring acoustic feature extraction, signal preprocessing, and GMM-based recognition systems with detailed algorithmic explanations
MATLAB code for speech recognition featuring a comprehensive graphical user interface (GUI)
A speech recognition program implementing the DTW algorithm for isolated digit recognition, featuring dynamic time warping for improved accuracy in temporal pattern matching.
MATLAB simulation for speech recognition with comprehensive documentation, featuring MFCC feature extraction and DTW algorithm for identifying 10 simple voice commands. Implementation includes code-level explanations of feature vector computation and pattern matching techniques.
A speech recognition program based on probabilistic neural network approach, implemented in MATLAB with valuable reference code examples and algorithmic implementations.
A comprehensive MATLAB toolbox for speech coding, speech compression, and speech recognition applications, featuring multiple algorithmic implementations and practical examples.