Using Second-Order Hidden Markov Model to Improve Speaker Identification Recognition Performance under Neutral Condition
Sound
2017-07-03 v1
Abstract
In this paper, second-order hidden Markov model (HMM2) has been used and implemented to improve the recognition performance of text-dependent speaker identification systems under neutral talking condition. Our results show that HMM2 improves the recognition performance under neutral talking condition compared to the first-order hidden Markov model (HMM1). The recognition performance has been improved by 9%.
Keywords
Cite
@article{arxiv.1706.09758,
title = {Using Second-Order Hidden Markov Model to Improve Speaker Identification Recognition Performance under Neutral Condition},
author = {Ismail Shahin},
journal= {arXiv preprint arXiv:1706.09758},
year = {2017}
}