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Efficient Implementation of the Room Simulator for Training Deep Neural Network Acoustic Models

By Chanwoo Kim and others at
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In this paper, we describe how to efficiently implement an acoustic room simulator to generate large-scale simulated data for training deep neural networks. Even though Google Room Simulator in [1] was shown to be quite effective in reducing the Word Error Rates (WERs) for far-field applications by generating simulated far-field... Show more
January 1, 2019
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Efficient Implementation of the Room Simulator for Training Deep Neural Network Acoustic Models
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