Background noise reduction via dual-channel scheme for speech recognition in vehicular environment

Sungjoo Ahn, Hanseok Ko

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


This paper concerns an effective dual-channel noise reduction method to increase the performance of robust speech recognition in vehicular environment While various single channel methods have already been developed and dual-channel methods have been studied somewhat, their effectiveness in real environments, such as in vehicular, has not yet been formally proven in terms of achieving acceptable performance level. Our aim is to remedy the low performance of the single and dual-channel noise reduction methods. In particular, we propose a dual-channel noise reduction method based on a high-pass filter and front-end processing of the eigendecomposition method. Representative experiments were conducted with a real multichannel car corpus and results were compared with respect to the microphones arrangements. From the analysis and results, we show that the enhanced eigendecomposition method combined with high-pass filter indeed significantly improves the speech recognition performance under dual-channel environment.

Original languageEnglish
Article number11.4-4
Pages (from-to)461-462
Number of pages2
JournalDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Publication statusPublished - 2005
Event2005 Digest of Technical Papers - International Conference on Consumer Electronics, ICCE 2005 - Las Vegas, NV, United States
Duration: 2005 Jan 82005 Jan 12

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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