Out-of-vocabulary rejection based on selective attention model

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Based on a psychological selective attention theory a new algorithm is developed to provide reliable out-of-vocabulary (OOV) rejection for speech recognition systems in noisy environments. The developed attention model is based on Broadbent's 'early filtering' theory, and the attention adaptation process utilizes a gradient-descent error minimization algorithm with error backpropagation rule. The developed model is applied to isolated-word recognition tasks, and much higher in-vocabulary recognition rates are achieved with the same out-of-vocabulary rejection rates.
Publisher
KLUWER ACADEMIC PUBL
Issue Date
2000-08
Language
English
Article Type
Article
Keywords

RECOGNITION

Citation

NEURAL PROCESSING LETTERS, v.12, no.1, pp.41 - 48

ISSN
1370-4621
URI
http://hdl.handle.net/10203/69186
Appears in Collection
EE-Journal Papers(저널논문)
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