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has been cited by the following article:

• TITLE: A New Method of Voiced/Unvoiced Classification Based on Clustering

  AUTHORS: Mojtaba Radmard, Mahdi Hadavi, Mohammad Mahdi Nayebi

  KEYWORDS: Speech, Voiced, Unvoiced, Clustering, Cepstrum, Autocorrelation, Zero crossing

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.2 No.4, November 16, 2011

  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.