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Reverberation is a phenomenon observed in almost all enclosed environments. Human listeners rarely experience problems in comprehending speech in reverberant environments, but automatic speech recognition (ASR) systems often suffer increased error rates under such conditions. In this work, we explore the role of robust acoustic features motivated by human speech perception studies, for building ASR...
Convolutional deep neural networks (CDNNs) have consistently shown more robustness to noise and background contamination than traditional deep neural networks (DNNs). For speech recognition, CDNNs apply their convolution filters across frequency, which helps to remove cross-spectral distortions and, to some extent, speaker-level variability stemming from vocal tract length differences. Convolution...
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