Speaker identification using discrete wavelet packet transform technique with irregular decomposition |
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| Authors: | Jian-Da Wu Bing-Fu Lin |
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| Affiliation: | 1. High Voltage Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Politechniou Street, Zografou Campus, Athens 15780, Greece;2. School of Mathematics, Statistics and Actuarial Science, University of Kent, Cornwallis Building, P.O. CT2 7NF, Canterbury, UK;3. Management & Decision Engineering Lab, Department of Financial and Management Engineering, University of the Aegean, 41 Kountouriotou Street, 82100 Chios, Greece;1. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, 721302, India;2. Advanced Technology Development Centre, Indian Institute of Technology Kharagpur, 721302, India |
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| 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. |
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