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A Convolutional Recurrent Neural Network for Real-Time ...

Interspeech 2018. 2-6 September 2018, Hyderabad A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement Ke Tan1 , DeLiang Wang1,2. 1. Department of Computer Science and Engineering, The Ohio State University, USA. 2. Center for Cognitive and Brain Sciences, The Ohio State University, USA. Abstract speech [6] [7]. In this study, we use the magnitude spectra of target speech as the training target. Many real-world applications of speech enhancement, such as For supervised speech enhancement, noise generalization hearing aids and cochlear implants, desire Real-Time processing, and speaker generalization are both crucial. A simple yet ef- with no or low latency. In this paper, we propose a novel convo- fective method to deal with noise generalization is to train with lutional Recurrent Network (CRN) to address Real-Time monaural different noise types [8]. Analogously, to address speaker gen- speech enhancement.

A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement Ke Tan 1, DeLiang Wang 1 ;2 1 Department of Computer Science and Engineering, The Ohio State University, USA 2 Center for Cognitive and Brain Sciences, The Ohio State University, USA tan.650@osu.edu, wang.77@osu.edu Abstract Many real-world applications of speech …

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