SNR Classification System Based on Classification of Voiced/Unvoiced Signal
نویسنده
چکیده
This paper proposes a signal-to-noise ratio (SNR) classification system based on a classification of voiced/unvoiced signal using a time-delay neural network for noise reduction in speech that is degraded by background noises. As such, the proposed system detects voiced and unvoiced sections, then reduces the noise signal for each input frame using the time-delay neural network.
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تاریخ انتشار 2013