LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

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Title Automatic Speech Segmentation in High Noise Condition

Authors Ivanov Rosen (Department “Computer Systems and Technologies”, Technical University, 4 “H.Dimitar”, 5300 Gabrovo, Bulgaria, rosen@tugab.bg)

Keywords

Session Session SP4 - Tools for Evaluation and Processing of Spoken Language Resources

Abstract The accurate segmentation of speech and end points detection in adverse condition is very important for building robust automatic speech recognition (ASR) systems. Segmentation of speech is not a trivial process - in high noise conditions it is very difficult to determine weak fricatives and nasals at end of the words. An efficient threshold (a priory defined) independent speech segmentation algorithm, robust to level of disturbance signals, is developed. The results show a significant improvement of robustness of proposed algorithm with respect to traditional algorithms.

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Title	Automatic Speech Segmentation in High Noise Condition
Authors	Ivanov Rosen (Department “Computer Systems and Technologies”, Technical University, 4 “H.Dimitar”, 5300 Gabrovo, Bulgaria, rosen@tugab.bg)
Keywords
Session	Session SP4 - Tools for Evaluation and Processing of Spoken Language Resources
Abstract	The accurate segmentation of speech and end points detection in adverse condition is very important for building robust automatic speech recognition (ASR) systems. Segmentation of speech is not a trivial process - in high noise conditions it is very difficult to determine weak fricatives and nasals at end of the words. An efficient threshold (a priory defined) independent speech segmentation algorithm, robust to level of disturbance signals, is developed. The results show a significant improvement of robustness of proposed algorithm with respect to traditional algorithms.