文件名称:08-NTAV-SPA_165_Marciniak-Rochowniak-etal
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In this paper we propose a method for voice
activity detection (VAD) in a speech signal recorded in the
presence of noise. The so-called endpoint detection (EPD),
i.e., detection of voice activity (speech) boundaries is very
difficult if the signal is acquired in noisy environments. The
proposed VAD method uses an additional stage of wavelet
subband denoising. We compared this approach with other
standard methods i.e.: zero-crossing rate and spectral
entropy analysis. Additionally we present in this paper our
basic results illustrating the main aim of this contribution,
consisting in application of intelligent denoising strategies
to various VAD algorithms.
activity detection (VAD) in a speech signal recorded in the
presence of noise. The so-called endpoint detection (EPD),
i.e., detection of voice activity (speech) boundaries is very
difficult if the signal is acquired in noisy environments. The
proposed VAD method uses an additional stage of wavelet
subband denoising. We compared this approach with other
standard methods i.e.: zero-crossing rate and spectral
entropy analysis. Additionally we present in this paper our
basic results illustrating the main aim of this contribution,
consisting in application of intelligent denoising strategies
to various VAD algorithms.
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08-NTAV-SPA_165_Marciniak-Rochowniak-etal.pdf