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A New Method of Voiced/Unvoiced Classification Based on Clustering
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
- 1 Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
- 2 Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
- 3 Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Journal of Signal and Information Processing·Volume 02 (2011)·Pages 336–347·Published 29 November 2011·DOI10.4236/jsip.2011.24048
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Abstract
In this paper, a new method for making v/uv decision is developed which uses a multi-feature v/uv classification algorithm based on the analysis of cepstral peak, zero crossing rate, and autocorrelation function (ACF) peak of short-time segments of the speech signal by using some clustering methods. This v/uv classifier achieved excellent results for identification of voiced and unvoiced segments of speech.
KeywordsSpeechVoicedUnvoicedClusteringCepstrumAutocorrelationZero crossing
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