The Complexity Analysis of Voiced and Unvoiced Speech Signal Based on Sample Entropy
- Resource Type
- Conference
- Authors
- Sun, Guiqi; Fan, Zhenyan; Mastorakis, Nikos E.; Kaminaris, Stavros D.; Zhuang, Xiaodong
- Source
- 2017 Fourth International Conference on Mathematics and Computers in Sciences and in Industry (MCSI) MCSI Mathematics and Computers in Sciences and in Industry (MCSI), 2017 Fourth International Conference on. :26-29 Aug, 2017
- Subject
- Computing and Processing
Entropy
Speech
Complexity theory
Speech processing
Vibrations
Acoustics
voiced/unvoiced classification
sample entropy
signal complexity
speech processing
- Language
The difference of signal complexity for voiced/unvoiced speech is studied. The sample entropy is estimated for a group of single phoneme pronunciations. The experimental data indicates that voiced and unvoiced pronunciations are different in signal complexity, which proves the effectiveness of the sample entropy feature for voiced/unvoiced classification.