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In this paper, a new approach to online Speech Activity Detection (SAD) is proposed. This approach is designed for the use in a system that carries out 24/7 transcription of radio/TV broadcasts containing a large amount of non-speech segments, such as advertisements or music. To improve the robustness of detection, we adopt Deep Neural Networks (DNNs) trained on artificially created mixtures of speech...
This paper deals with utilization of deep neural networks (DNNs) for speech recognition. The main goal is to find out the best strategy for training and utilization of these models within an acoustic modeling module of a large vocabulary continuous speech recognition (LVCSR) system of Czech language. For this purpose, various DNNs are trained a) using several training strategies, b) with different...
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