Boris Simák

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This paper presents an alternative energy-based algorithm to provide speech/silence classification. The algorithm is capable to track non-stationary signals and dynamically calculate instantaneous value for threshold using adaptive scaling parameter. It is based on the observation of a noise power estimation used for computation of the threshold can be(More)
An alternative low-complexity method to identify voice and silence regions in a speech signal is introduced in this paper. Its performance, limitations, and some other voice classification techniques which deal with energy estimation are presented as well. The proposed algorithm uses periodicity measure, highfrequency to low-frequency signal energy ratio,(More)
This paper describes pitch tracking techniques, which combine voiced/unvoiced classification and pitch estimation based on cepstral analysis, time autocorrelation, spectro-temporal autocorrelation (STA) and average magnitude difference function (AMDF). Preand post processing techniques improving performance of pitch detection algorithms (PDAs) are also(More)