Clustering based Voiced-Unvoiced-Silence Detection in Speech using Temporal and Spectral Parameters

被引：0

作者：

Mondal, Sujoy ^{[1
]}

Das Barman, Abhirup ^{[2
]}

机构：

[1] RCC Inst Informat Technol, Dept ECE, Kolkata, India

[2] Univ Calcutta, Inst Radio Phys & Elect, Kolkata, India

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN) | 2015年

关键词：

Gaussian similarity function; Spectral Clustering; TIMIT database; Voiced unvoiced silence detection;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper reports automatic segmentation of voiced, unvoiced and silence portion of speech on TIMIT data base. Waveform and frequency domain parameters are used to form multi dimensional feature space. Short time energy threshold of unvoiced segment is used to separate out silence or background from speech. The Gaussian similarity function based spectral clustering is used to find error performance of voiced/unvoiced (V/UV) portion of the speech. The classification accuracy of V/UV is measured and the result is compared with the other techniques available in the literatures. The proposed technique provides at least 98.3% V/UV detection accuracy.

引用

页码：390 / 394

页数：5

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