Exploiting Sequential Phonetic Constraints in Recognizing Spoken Words

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6434

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DC Field	Value	Language
dc.creator	Huttenlocher, Daniel P.	-
dc.date	2004-10-04T14:56:14Z	-
dc.date	2004-10-04T14:56:14Z	-
dc.date	1985-10-01	-
dc.date.accessioned	2013-10-09T02:45:26Z	-
dc.date.available	2013-10-09T02:45:26Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-867	-
dc.identifier	http://hdl.handle.net/1721.1/6434	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	Machine recognition of spoken language requires developing more robust recognition algorithms. The current paper extends the work of Shipman and Zue by investigating the power of partial phonetic descriptions. First we demonstrate that sequences of manner of articulation classes are more reliable and provide more constraint than other classes. Alone these are of limited utility, due to the high degree of variability in natural speech. This variability is not uniform, however, as most modifications and deletions occur in unstressed syllables. The stressed syllables provide substantially more constraint. This indicates that recognition algorithms can be made more robust by exploiting the manner of articulation information in stressed syllables.	-
dc.format	3921047 bytes	-
dc.format	1455850 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-867	-
dc.title	Exploiting Sequential Phonetic Constraints in Recognizing Spoken Words	-
Appears in Collections:	MIT Items

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