标题:A Novel Speech Endpoint Detection Based on Multiple Complexities and Fuzzy C Means
作者:Wu, Chuanyan; Gao, Rui; Lin, Bentao
通讯作者:Wu, CY
作者机构:[Wu, Chuanyan; Gao, Rui] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Shandong, Peoples R China.; [Lin, Bentao] JiNan Semicond Lab, Jinan 25 更多
会议名称:Chinese Automation Congress (CAC)
会议日期:OCT 20-22, 2017
来源:2017 CHINESE AUTOMATION CONGRESS (CAC)
出版年:2017
页码:6369-6372
关键词:speech endpoint detection; LZ complexity; C0 complexity; fluctuation; complexity; fuzzy C-means
摘要:Accurate Speech endpoint detection is important for speaker recognition, speech recognition, coding, and transmission and so on. In this paper, a fusion feature is proposed for speech endpoint detection, which utilized zero-crossing rate, Lempel and Ziv complexity (LZC), C-0, complexity and fluctuation complexity to represent the speech signal. In order to classify speech signal and background signal, the fuzzy c-means (ECM) is adopted as the classification. Experiments are carried out with white noise of NOISE-92 database to demonstrate the efficiency of the proposed method. Experimental results show that the proposed method can detect endpoints accurately.
收录类别:CPCI-S
资源类型:会议论文
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