Author(s)

Mojtaba Radmard, Mahdi Hadavi, Mohammad Mahdi Nayebi

Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.

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.

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

M. Radmard, M. Hadavi and M. Nayebi, "A New Method of Voiced/Unvoiced Classification Based on Clustering," Journal of Signal and Information Processing, Vol. 2 No. 4, 2011, pp. 336-347. doi: 10.4236/jsip.2011.24048.