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J. K. Shah, A. N. Iyer, B. Y. Smolenski and R. E. Yantorno, “Robust Voiced/Unvoiced Classification Using Novel Features and Gaussian Mixture Model,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, 2004, pp. 17-21.

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.