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A multi-filter system for speech enhancement under low signal-to-noise ratios
- Source :
- Journal of Industrial & Management Optimization. 5:671-682
- Publication Year :
- 2009
- Publisher :
- American Institute of Mathematical Sciences (AIMS), 2009.
-
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.
- Subjects :
- Control and Optimization
Voice activity detection
Computer science
Applied Mathematics
Strategy and Management
Speech recognition
Noise reduction
Speech coding
Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)
Linear predictive coding
Speech processing
Hybrid algorithm
Atomic and Molecular Physics, and Optics
Speech enhancement
Filter system
Computer Science::Sound
Business and International Management
Electrical and Electronic Engineering
Subjects
Details
- ISSN :
- 1553166X
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- Journal of Industrial & Management Optimization
- Accession number :
- edsair.doi...........e5f59ae67481c39e1e3be7e047d54ec2