This paper deals with the issues associated with the dereverberation of speech or audio signals using deep neural networks (DNNs). They include feature extraction for DNNs from both clean and reverberant signals and DNN construction for generating dereverberant signals. To evaluate the performance of the proposed dereverberation method, artificially processed reverberant speech signals are obtained and a feed-forward DNN is constructed. It is shown that log spectral distortion (LSD) after applying DNN-based dereverberation is reduced by around 1.9 dB, compared with that of reverberant speech signals.

Authors: Park, Ji Hyun; Jeon, Kwang Myung; Chun, Chanjun; Yoo, Ji Sang; Kim, Hong Kook
Affiliations: Gwangju Institute of Science and Technology (GIST), Gwangju, Korea; Kwangwoon University, Seoul, Korea(See document for exact affiliation information.)
AES Convention: 141 (September 2016) eBrief:300
Publication Date: September 20, 2016
Subject: Education, Network Audio, & Signal Processing

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