Binaural speech enhancement method by wavelet transform based on interaural level and argument differences

Satoshi Hongo, Shuichi Sakamoto, Yoiti Suzuki

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

1 Citation (Scopus)

Abstract

Human binaural processing might enhance signal sounds in noisy environments. Binaural speech enhancement with two outputs facilitates merits of both signal processing itself and that by human binaural processing. Most previous studies in this area have implemented signal processing in the time and frequency domains. The use of wavelet transform (WT) appears to be promising because it has a scale domain whose bandwidth is inversely proportional to the scale level. Therefore, it might well be compared to auditory filters. In this paper, a new binaural speech enhancement algorithm applying Complex Wavelet Transform is proposed. Experiments of objective and subjective evaluations with a directional target signal and an interference sound source generated by convolving HRTFs were conducted to demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of 2012 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2012
Pages290-295
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2012 - Xian, Shaanxi, China
Duration: 2012 Jul 152012 Jul 17

Publication series

NameInternational Conference on Wavelet Analysis and Pattern Recognition
ISSN (Print)2158-5695
ISSN (Electronic)2158-5709

Other

Other2012 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2012
Country/TerritoryChina
CityXian, Shaanxi
Period12/7/1512/7/17

Keywords

  • Cocktail party effects
  • ELD
  • Hearing aids
  • IAD
  • Multiple-noise-source

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Binaural speech enhancement method by wavelet transform based on interaural level and argument differences'. Together they form a unique fingerprint.

Cite this