MATLAB Code Implementation for Voice Recognition
A MATLAB-based voice recognition program capable of identifying different speakers' voices through signal processing algorithms.
Isolated Word Speech Recognition Using DTW Algorithm
MATLAB implementation of isolated word speech recognition system based on Dynamic Time Warping (DTW) with feature extraction and pattern matching capabilities
Speech Recognition Using Artificial Neural Networks
This project implements speech recognition by combining LPC (Linear Predictive Coding) parameters extracted from audio signals with artificial neural networks for classification. The implementation demonstrates feature extraction techniques and neural network architecture suitable for speech pattern recognition.
Calculation Method of LPCC (Linear Predictive Cepstral Coefficients) in Speech Recognition
This source code implements the calculation method of LPCC (Linear Predictive Cepstral Coefficients) for speech recognition applications. The implementation has been experimentally verified as functional. To enhance understanding, critical statements and numerical values are accompanied by detailed comments explaining the algorithmic steps and parameter significance.
Blind Signal Processing for Speech Recognition
Implementation of blind signal processing algorithms for speech recognition using MATLAB development environment with comprehensive code examples
MATLAB Implementation of Hidden Markov Model (HMM) for Speech Recognition
MATLAB-based implementation of Hidden Markov Model (HMM), a crucial technique in speech recognition systems, featuring algorithm explanation and practical code examples
Vector Quantization (VQ) Implementation for Speech Recognition in MATLAB
MATLAB code implementation of Vector Quantization (VQ) for speech recognition systems, featuring signal vectorization and similarity matching algorithms with practical applications
Speech Recognition Implementation Using MATLAB
Speech recognition system developed in MATLAB using custom collected datasets, featuring audio signal processing and speech-to-text conversion algorithms
High-Performance Speech Recognition System
An advanced speech recognition system with exceptional accuracy rates, featuring implementation insights and best practices for developers.
HMM-based Speech Recognition in Noisy Environments Using hmm Files
The hmm files implement Hidden Markov Model (HMM) algorithm for speech recognition under noisy conditions. Key components include: vad.m for endpoint detection using energy-based thresholding; mfcc.m for Mel-Frequency Cepstral Coefficients extraction with filter bank processing; pdf.m computing Gaussian probability density output for observation vectors; mixture.m calculating state output probabilities through Gaussian mixture modeling; getparam.m deriving forward/backward probabilities and scaling coefficients; viterbi.m implementing Viterbi algorithm for optimal path decoding; baum.m executing Baum-Welch algorithm for parameter re-estimation; inithmm.m initializing HMM parameters; train.m handling model training procedures.