%0 Journal Article
%T A New Method of Voiced/Unvoiced Classification Based on Clustering
%A Mojtaba Radmard
%A Mahdi Hadavi
%A Mohammad Mahdi Nayebi
%J Journal of Signal and Information Processing
%P 336-347
%@ 2159-4481
%D 2011
%I Scientific Research Publishing
%R 10.4236/jsip.2011.24048
%X 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.
%K Speech
%K Voiced
%K Unvoiced
%K Clustering
%K Cepstrum
%K Autocorrelation
%K Zero crossing
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=8458