Wavelet-based dynamic time warping

被引：7

作者：

Barbon, Sylvio, Jr. ^{[1
]}

Guido, Rodrigo Capobianco ^{[1
]}

Vieira, Lucimar Sasso ^{[1
]}

Fonseca, Everthon Silva ^{[2
]}

Sanchez, Fabricio Lopes ^{[2
]}

Scalassara, Paulo Rogerio ^{[2
]}

Maciel, Carlos Dias ^{[2
]}

Pereira, Jose Carlos ^{[2
]}

Chen, Shi-Huang ^{[3
]}

机构：

[1] Univ Sao Paulo, Inst Phys, BR-13566590 Sao Carlos, SP, Brazil

[2] Univ Sao Paulo, Sch Engn, BR-13566590 Sao Carlos, SP, Brazil

[3] Shu Te Univ, Dept Comp Sci & Informat Engn, Kaohsiung 824, Taiwan

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2009年 / 227卷 / 02期

关键词：

Dynamic time warping; Discrete wavelet transform; Pattern recognition in spoken language;

D O I：

10.1016/j.cam.2008.03.015

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：271 / 287

页数：17

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