NDLI: An automotive application of real-time adaptive Wiener filter for non-stationary noise cancellation in a car environment

Content Provider	IEEE Xplore Digital Library
Author	Yen-Hsiang Chen Shanq-Jang Ruan Qi, T.
Copyright Year	2012
Description	Author affiliation: Department of Electronic Engineering, National Taiwan University of Science and Technology, Taiwan (Yen-Hsiang Chen; Shanq-Jang Ruan) \|\| School of Architecture, Building and Engineering, Otago Polytechnic, New Zealand (Qi, T.)
Abstract	Wiener filter is one of the most fundamental noise-reduction approaches among numerous techniques. The speech recognition in an in-vehicle environment needs a non-stationary noise cancellation to eliminate the background noise. However, few efforts have been reported to show the effectiveness of Wiener filter. Not much has been evaluated how the Wiener filter really works for reducing the non-stationary noise in real-time. In this paper, a real-time adaptive Wiener filter with two microphones is implemented to reduce noisy speech when noise signals and desired speech are incoming simultaneously. Furthermore, in order to build a real-time noise canceller, this paper also gives an analysis of different matrix sizes of the Wiener filter so as to enable the possibility of real-time implementation. The performance of the proposed design is measured by as much as 20dB noise reduction, and the proposed adaptive Wiener matrix update speed achieves a 28.6 ms/frame, with a matrix size of 200.
Starting Page	597
Ending Page	601
File Size	1079604
Page Count	5
File Format	PDF
ISBN	9781467321921
e-ISBN	9781467321938
DOI	10.1109/ICSPCC.2012.6335628
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wiener filter Speech Noise cancellation Real-time systems Noise measurement Microphones Signal to noise ratio
Content Type	Text
Resource Type	Article

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