Document Detail

Vowel place detection for a knowledge-based speech recognition system.
MedLine Citation:
PMID:  18530576     Owner:  NLM     Status:  In-Data-Review    
This work aims to detect vowel place as part of a knowledge-based speech recognition system. Vowel place was classified into 6 groups based on tongue advancement [FrontBack] and height [HighMidLow]. Experiments were performed using 300 hVd utterance data from Hillenbrand [J. Acoust. Soc. Am. 97, 3099-3111] and 6600 TIMIT vowels. Features used include fundamental frequency (F0) and formant value (F1F3), where formant measurements were classified into separate groups using F0 measurements. The nearest class was found using a simple Mahalanobis distance measure, and yielded a 91.5% classification rate for the hVd data. The results for the TIMIT data were 64.4%, and error analysis with regard to adjacent segment manner and place was carried out to observe the effects of coarticulation, which was not observed in the hVd data.
Sukmyung Lee; Jeung-Yoon Choi
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of the Acoustical Society of America     Volume:  123     ISSN:  1520-8524     ISO Abbreviation:  J. Acoust. Soc. Am.     Publication Date:  2008 May 
Date Detail:
Created Date:  2008-06-05     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7503051     Medline TA:  J Acoust Soc Am     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3330     Citation Subset:  IM    
Yonsei University, 134 Sinchon-dong, Seodaemun-gu, 120-749 Seoul, Republic of Korea,
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