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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/18357

Title: Speaker Identification Using Discrete Wavelet Packet Transform Technique with Irregular Decomposition
Authors: Wu, Jian-Da;Lin, Bing-Fu
Contributors: 車輛科技研究所
Keywords: Speaker identification;Discrete wavelet transform;Wavelet packet transform;General regressive neural network
Date: 2009-03
Issue Date: 2014-04-29T07:28:09Z
Publisher: Elsevier Ltd
Abstract: This paper presents the study of speaker identification for security systems based on the energy of speaker utterances. The proposed system consisted of a combination of signal pre-process, feature extraction using wavelet packet transform (WPT) and speaker identification using artificial neural network. In the signal pre-process, the amplitude of utterances, for a same sentence, were normalized for preventing an error estimation caused by speakers’ change in volume. In the feature extraction, three conventional methods were considered in the experiments and compared with the irregular decomposition method in the proposed system. In order to verify the effect of the proposed system for identification, a general regressive neural network (GRNN) was used and compared in the experimental investigation. The experimental results demonstrated the effectiveness of the proposed speaker identification system and were compared with the discrete wavelet transform (DWT), conventional WPT and WPT in Mel scale.
Relation: Expert Systems with Applications, 36(2)Part2: 3136-3143
Appears in Collections:[車輛科技研究所] 期刊論文

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