Speech enhancement using square microphone array for mobile devices

Shintaro Takada*, Tetsuji Ogawa, Kenzo Akagiri, Tetsunori Kobayashi

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

In this paper, we propose a new type of speech enhancement method that is suitable for mobile devices used in noisy environments. For the sake of achieving high-performance speech recognition and auditory perception in the mobile devices, disturbance noises have to be removed under the requirements of a space-saving microphone arrangement and a low computational cost. The proposed method can reduce both the directional and the diffuse noises under the requirements for the mobile devices by applying the square microphone array and the low-cost processing that consists of multiple null beam-forming, their minimum power channel selection and Wiener filtering. The effectiveness of the proposed method is clarified for speech recognition accuracies and speech qualities under the condition in which both the directional and the diffuse noises exist simultaneously: it reduced 40% of recognition errors and improved PESQ-based MOS value by 0.75 point.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages313-316
Number of pages4
DOIs
Publication statusPublished - 2008 Sept 16
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 2008 Mar 312008 Apr 4

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period08/3/3108/4/4

Keywords

  • Array signal processing
  • Mobile devices
  • Speech enhancement
  • Speech recognition
  • Wiener tittering

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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