A New Method of Voiced/Unvoiced Classification Based on Clustering

نویسندگان

  • Mojtaba Radmard
  • Mahdi Hadavi
  • Mohammad Mahdi Nayebi
چکیده

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.

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تاریخ انتشار 2012