Complex-valued temporal convolutional network for speech enhancement

Author:

Song Jiaqi1ORCID,Zou Lian1ORCID,Zhou Liqing1ORCID,Liu Ziao1ORCID,Fan Cien1ORCID,Wang Bin2ORCID

Affiliation:

1. Electronic Information School, Wuhan University, Wuhan, Hubei 430070, P. R. China

2. Hubei Three Gorges Laboratory, Yichang, Hubei 443000, P. R. China

Abstract

In this study, we introduce a novel approach to speech enhancement through the design of a complex temporal convolutional network (Complex-TCN). This model leverages the power of complex networks, enabling the simultaneous capture of both magnitude and phase information inherent in speech signals. By employing a temporal convolutional network, the Complex-TCN excels at extracting contextual information within the time domain of speech. Our findings underscore the substantial performance improvements achieved through the synergistic use of the temporal convolutional network and the incorporation of complex representations.

Funder

Hubei Three Gorges Laboratory

Publisher

World Scientific Pub Co Pte Ltd

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