Audio-visual speech enhancement using deep neural networks

Jen Cheng Hou, Syu Siang Wang, Ying Hui Lai, Jen Chun Lin, Yu Tsao, Hsiu Wen Chang, Hsin Min Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

This paper proposes a novel framework that integrates audio and visual information for speech enhancement. Most speech enhancement approaches consider audio features only to design filters or transfer functions to convert noisy speech signals to clean ones. Visual data, which provide useful complementary information to audio data, have been integrated with audio data in many speech-related approaches to attain more effective speech processing performance. This paper presents our investigation into the use of the visual features of the motion of lips as additional visual information to improve the speech enhancement capability of deep neural network (DNN) speech enhancement performance. The experimental results show that the performance of DNN with audio-visual inputs exceeds that of DNN with audio inputs only in four standardized objective evaluations, thereby confirming the effectiveness of the inclusion of visual information into an audio-only speech enhancement framework.

Original languageEnglish
Title of host publication2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789881476821
DOIs
StatePublished - 17 Jan 2017
Event2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of
Duration: 13 Dec 201616 Dec 2016

Publication series

Name2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016

Conference

Conference2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Country/TerritoryKorea, Republic of
CityJeju
Period13/12/1616/12/16

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