Detection Error Tradeoff (DET) Curve Analysis for Speaker Recognition Systems
Implementation and Analysis of False Acceptance Rate vs False Rejection Rate (DET Curve) in Speaker Recognition Algorithms
Speaker Recognition Using DTW Dynamic Time Warping with MATLAB Voice Toolbox
This self-developed speaker recognition system utilizes MATLAB's Voice Toolbox and DTW Dynamic Time Warping algorithm, demonstrating high recognition accuracy through efficient voice signal processing and pattern matching techniques.
MATLAB Implementation of Speaker Recognition with Neural Network Model
Speaker recognition code implementation featuring endpoint detection, pre-emphasis, MFCC feature extraction, and neural network classification model
Parameter Extraction for LPCC and MFCC in Speaker Recognition
Implementation of LPCC and MFCC parameter extraction algorithms for speaker recognition systems with code examples
Speaker Recognition Using VQ Algorithm
Implementing speaker recognition with VQ algorithm achieves excellent performance through feature vector quantization and pattern matching techniques.
Speaker Recognition Using GMM with MFCC Features
Implementation of speaker identification using MFCC feature extraction and Gaussian Mixture Model (GMM) with code-level implementation insights
Speaker Recognition Implementation Using Gaussian Mixture Models
Source code for speaker recognition utilizing Gaussian Mixture Models with excellent recognition performance, featuring feature extraction and model training implementation
MATLAB-Based Speaker Recognition and Verification System
This is a comprehensive speaker recognition and verification system developed using MATLAB, implementing advanced audio signal processing and pattern recognition algorithms for accurate speaker identification.
A Simple Speaker Recognition System with MATLAB Implementation
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 (Mel-Frequency Cepstral Coefficients) for feature extraction and GMM (Gaussian Mixture Models) for pattern matching, providing a comprehensive solution with additional modules for error handling and user interface.
Speaker Recognition Using Hidden Markov Model (HMM) with Speech Signal Processing Toolbox
Implementation of speaker recognition system based on Hidden Markov Model (HMM) utilizing speech signal processing toolbox, featuring model training with Baum-Welch algorithm and recognition via Viterbi decoding. Contact: lishicheng64@126.com