Professional MATLAB source code with comprehensive documentation and examples
Implementation of LBG algorithm for speech signal vector quantization. This package contains two main scripts: training.m processes training data to generate four initial codebooks using iterative splitting methodology, while quantizing.m performs ve
MFCC parameter extraction is crucial in speech recognition systems, offering both efficient storage and compatibility with human auditory perception. This MATLAB simulation code provides complete and high-performance feature extraction functionality,
MATLAB source code implementation for Linear Predictive Coding (LPC) spectral estimation of speech signals, featuring signal processing algorithms and key function implementations.
MATLAB program for speech enhancement using adaptive filtering algorithms, includes noisy speech samples. Simply modify the filename in the M-file for immediate use, with implementation featuring adjustable filter parameters and real-time processing
An overview of multiple speech enhancement techniques including MMSE algorithms, Wiener filtering, and masking enhancement with code implementation insights
Record an audio signal, perform time-frequency analysis, and play back the audio. Detailed implementation steps including code annotation and key MATLAB functions will be explained.
Speech separation program optimized for maximum signal-to-noise ratio, featuring implementation details suitable for technical adaptation
Robust voice activity detection algorithm based on adaptive sub-band spectral entropy with enhanced code implementation details
This document contains various algorithms used in speech recognition systems, including frame-based processing algorithms, MFCC (Mel-Frequency Cepstral Coefficients) computation, and cepstral analysis algorithms, all implemented using MATLAB. The pac
A Wiener filtering program designed for speech signal enhancement, featuring comprehensive technical documentation and efficient noise reduction capabilities
LMS and RLS algorithms in adaptive signal processing are highly suitable for research in speech enhancement and noise reduction applications
MATLAB code implementation of Butterworth filter for audio signal processing, featuring comparison with other filter types and detailed algorithmic explanations
This program designs and implements a basic speaker recognition system using MATLAB. Key functional modules include speech signal input management, feature extraction for speech discrimination, and speaker authentication. The system utilizes MFCC (Me
AMUSE - An Independent Component Analysis (ICA) Algorithm for Blind Separation of Mixed Speech Signals, implementing second-order statistics and time-delayed covariance matrices for source separation
Speech signals, though time-varying and non-stationary stochastic processes, can be approximated as stationary over short time intervals. Speech enhancement can be achieved by estimating the short-time spectrum of "clean" speech from the noisy speech
A practical MATLAB program for audio recording with comprehensive code descriptions and implementation details. Download now to get started!
Classical estimation of MELP (Mixed Excitation Linear Prediction) in speech coding with MATLAB implementation guide
MATLAB implementation for pitch frequency extraction from speech signals using autocorrelation and cepstral analysis methods with configurable frame size and windowing options.
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
Implementation of Linear Predictive Coding for speech signals, featuring a main program that orchestrates four subprograms handling prediction analysis, quantization, encoding, and decoding functionalities.