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dc.contributor.authorGutkin, Alexander
dc.contributor.authorKing, Simon
dc.date.accessioned2006-05-09T11:46:37Z
dc.date.available2006-05-09T11:46:37Z
dc.date.issued2005
dc.identifier.citationIn Hugo Gamboa and Ana Fred, editors, Proc. 5th International Workshop on Pattern Recognition in Information Systems (PRIS-2005), In conjunction with the 7th International Conference on Enterprise Information Systems (ICEIS-2005), pages 43-51, Miami, USA, May 24-25 2005en
dc.identifier.urihttp://hdl.handle.net/1842/932
dc.description.abstractThis paper deals with formulation of alternative structural approach to the speech recognition problem. In this approach, we require both the representation and the learning algorithms defined on it to be linguistically meaningful, which allows the speech recognition system to discover the nature of the linguistic classes of speech patterns corresponding to the speech waveforms. We briefly discuss the current formalisms and propose an alternative - a phonologically inspired string-based inductive speech representation, defined within an analytical framework specifically designed to address the issues of class and object representation. We also present the results of the phoneme classification experiments conducted on the TIMIT corpus of continuous speech.en
dc.format.extent151728 bytes
dc.format.extent439203 bytes
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherINSTICC Pressen
dc.subjectspeechen
dc.subjectrecognitionen
dc.titleInductive String Template-Based Learning of Spoken Languageen
dc.typeConference Paperen


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