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Wavelet-based dynamic time warping
Authors:Sylvio Barbon Jr  Rodrigo Capobianco Guido  Lucimar Sasso Vieira  Everthon Silva Fonseca  Fabrício Lopes Sanchez  Paulo Rogério Scalassara  Carlos Dias Maciel  José Carlos Pereira  Shi-Huang Chen
Institution:1. Institute of Physics of São Carlos, University of São Paulo, USP, São Carlos, São Paulo 13566-590, Brazil;2. School of Engineering at São Carlos, University of São Paulo, USP, São Carlos, São Paulo 13566-590, Brazil;3. Department of Computer Science and Information Engineering, Shu-Te University, Kaohsiung County, 824, Taiwan, ROC
Abstract: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 that is based on the Discrete Wavelet Transform (DWT).
Keywords:Dynamic time warping  Discrete wavelet transform  Pattern recognition in spoken language
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