Improvement of power-spectral-subtraction algorithm using cross-term compensation for speech enhancement

Ching Ta Lu, Yung Yue Chen, Jun Hong Shen, Ling Ling Wang, Chung Lin Lei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Although the power-spectral-subtraction (PSS) algorithm is widely used in speech enhancement, this method suffers from musical residual noise. So the enhanced speech sounds annoying to the human ear. This study proposes using the cross term between the spectrum of speech and noise signals to be additionally subtracted from the power spectrum of noisy speech, enabling background noise to be efficiently removed. Experimental results show that the proposed method can significantly improve the performance of the PSS algorithm by the consideration on the cross term. The quantity of musical residual noise can be efficiently removed, while speech components are well preserved in the enhanced speech.

Original languageEnglish
Title of host publicationFrontier Computing - Theory, Technologies and Applications, FC 2016
EditorsNeil Y. Yen, Jason C. Hung
PublisherSpringer Verlag
Pages579-590
Number of pages12
ISBN (Print)9789811031861
DOIs
Publication statusPublished - 2018
Event 5th International Conference on Frontier Computing, FC 2016 - Tokyo, Japan
Duration: 2016 Jul 132016 Jul 15

Publication series

NameLecture Notes in Electrical Engineering
Volume422
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other 5th International Conference on Frontier Computing, FC 2016
CountryJapan
CityTokyo
Period16-07-1316-07-15

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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