NDLI: A Missing Data-based Feature Fusion Strategy for Noise-Robust Automatic Speech Recognition Using Noisy Sensors

Content Provider	IEEE Xplore Digital Library
Author	Demiroglu, C. Anderson, D.V. Clements, M.A.
Copyright Year	2007
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA (Demiroglu, C.; Anderson, D.V.; Clements, M.A.)
Abstract	Feature fusion is a popular approach for improving the accuracy of speech recognition systems in noisy environments. Although the feature fusion method performs well for high and moderate SNRs, its performance degrades rapidly at low SNRs. Moreover, auxiliary features that are robust to acoustic noise may sometimes be unreliable, because of sensor misplacements etc, which can further degrade the performance. Furthermore, noisy sensor signals may exist not only in the test data but also in the training data. Here, the feature fusion method is combined with a missing data technique to improve noise-robustness at low SNRs. An auxiliary feature is used both for feature fusion and for detecting the unreliable speech frames. Noisy auxiliary features are addressed using a missing data approach both in the decoding and training systems. In the experiments, substantial improvements in the feature fusion method are obtained especially at low SNRs. The proposed missing data-based training strategy is also shown to improve the accuracy significantly.
Starting Page	965
Ending Page	968
File Size	190586
Page Count	4
File Format	PDF
ISBN	1424409209
DOI	10.1109/ISCAS.2007.378087
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise robustness Automatic speech recognition Sensor fusion Acoustic noise Working environment noise Acoustic sensors Degradation Speech recognition Sensor phenomena and characterization Acoustic testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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