标题:A Study of Speech Feature Extraction Based on Manifold Learning
作者:Hao, Cheng; Xin, Ma; Xu, Yugong
通讯作者:Xin, M
作者机构:[Hao, Cheng; Xin, Ma; Xu, Yugong] Shandong Univ, Sch Informat Sci & Engn, Qingdao, Shandong, Peoples R China.
会议名称:International Symposium on Power Electronics and Control Engineering (ISPECE)
会议日期:DEC 28-30, 2018
来源:2018 INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS AND CONTROL ENGINEERING (ISPECE 2018)
出版年:2019
卷:1187
期:5
DOI:10.1088/1742-6596/1187/5/052021
摘要:Manifold learning is a nonlinear data dimension reduction method. It can look for the essence of things from the observed phenomena, and find the inherent law of data. Traditional MFCC feature will lead a slower learning speed on account of it has high dimension and useless noise. Therefore, a speech feature extraction method based on manifold learning is proposed. Firstly, we use the manifold learning dimension reduction algorithm for the dimension reduction of Mel features and then for vowels classification. In order to further demonstrate the effectiveness of manifold learning feature in speech recognition, we propose a fusion speech feature extraction method and apply it to the identification of Chinese isolated words. Experiments prove that the fusion feature extraction method has achieved a better result than that of traditional MFCC feature extraction method.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067676061&doi=10.1088%2f1742-6596%2f1187%2f5%2f052021&partnerID=40&md5=141e80dbc02a5c20c988600a2f941f4f
TOP