A multi-filter system for speech enhancement under low signal-to-noise ratios
Access Status
Authors
Date
2009Type
Metadata
Show full item recordCitation
Source Title
ISSN
Faculty
School
Collection
Abstract
In this paper, the problem of deteriorating performance of speech recognition under very low signal-to-noise ratios (SNR) is considered. In particular, for a given pre-trained speech recognizer and for a finite set of speech commands, we show that popular noise reduction methods have a mixed performance in speech recognition accuracy under very low SNR. Although most noise reduction methods are attempting to reduce speech distortion or to increase noise suppression, it does not necessarily improve speech recognition accuracy very much due to the complexity of the recognizer. We propose a new hybrid algorithm to optimize on the speech recognition accuracy directly by mixing different noise reduction methods together. We show that this method can indeed improve the accuracy significantly.
Related items
Showing items related by title, author, creator and subject.
-
Yiu, K.; Chan, Kit Yan; Grbić, N.; Nordholm, Sven (2012)In this paper, a new approach to designing beamformers for voice control device is proposed. It is well-known that under a strong near-field noise with low signal-to-noise ratios (SNR), the performance of speech recognition ...
-
Chan, Kit Yan; Yiu, Cedric K.F.; Dillon, Tharam S.; Nordholm, Sven; Ling, S.H. (2012)For over two decades, speech control mechanisms have been widely applied in manufacturing systems such as factory automation, warehouse automation and industrial robotic control for over two decades. To implement speech ...
-
Chan, Kit Yan; Nordholm, Sven; Yiu, Ka Fai; Togneri, R. (2013)Industrial automation with speech control functions is generally installed with a speech recognition sensor which is used as an interface for users to articulate speech commands. However, recognition errors are likely to ...