Speaker Recognition Using Hidden Markov Model (HMM) with Speech Signal Processing Toolbox
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Resource Overview
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
Detailed Documentation
For any inquiries or requirements regarding speaker recognition implementation using Hidden Markov Model (HMM) with speech signal processing toolbox, please feel free to contact me via email at lishicheng64@126.com. The system typically involves feature extraction (MFCC), HMM training using expectation-maximization, and likelihood comparison for speaker identification. I will respond promptly and provide assistance with code implementation, parameter optimization, or algorithmic explanations. Thank you for your interest and support!
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