DocumentCode :
312278
Title :
Lexical stress detection on stress-minimal word pairs
Author :
Ying, Goangshiuan S. ; Jamieson, Leah H. ; Chen, Ruxin ; Michell, Carl D. ; Liu, Hsin
Author_Institution :
Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
Volume :
3
fYear :
1996
fDate :
6-6 Oct. 1996
Firstpage :
1612
Abstract :
The authors present a study on the use of lexical stress classification to aid in the recognition of phonetically similar words. They use a simple pattern recognition approach to determine which syllable is lexically stressed for phonetically similar word pairs (e.g., PERfect, perFECT) extracted from continuously spoken sentences. They use a combination of two features from the acoustic correlates of lexical stress, and assume multivariate Gaussian distributions to form a Bayesian classifier. The features used are normalized energy and duration of the vowel for each syllable of the word. They evaluate several normalization methods. Two sets of sentences were designed for this study. For the pilot experiment, the classification accuracy on words from the natural sentence set was 89.9% and on words from the control sentence set was 100%. To improve the performance, three-feature classifiers, which included two normalized energy features and one normalized duration feature, were developed. The classification accuracy on words from the natural sentence set was 97.23%.
Keywords :
Bayes methods; Gaussian distribution; feature extraction; pattern classification; speech processing; speech recognition; Bayesian classifier; acoustic correlates; classification accuracy; continuously spoken sentences; control sentence set; lexical stress classification; lexical stress detection; lexically stressed syllable; multivariate Gaussian distributions; natural sentence set; normalized vowel duration; normalized vowel energy; pattern recognition approach; phonetically similar word pairs; phonetically similar word recognition; stress-minimal word pairs; three-feature classifiers; Bayesian methods; Detectors; Gaussian distribution; Hidden Markov models; Pattern recognition; Speech analysis; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA, USA
Print_ISBN :
0-7803-3555-4
Type :
conf
DOI :
10.1109/ICSLP.1996.607932
Filename :
607932
Link To Document :
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