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dc.contributor.authorChiu, Tzu-Hsuanen_US
dc.contributor.authorChiang, Chen-Yuen_US
dc.contributor.authorLiao, Yuan-Fuen_US
dc.contributor.authorYang, Jyh-Heren_US
dc.contributor.authorWang, Yih-Ruen_US
dc.contributor.authorChen, Sin-Horngen_US
dc.date.accessioned2014-12-08T15:33:16Z-
dc.date.available2014-12-08T15:33:16Z-
dc.date.issued2012en_US
dc.identifier.isbn978-7-5608-4869-3en_US
dc.identifier.urihttp://hdl.handle.net/11536/23150-
dc.description.abstractA study on introducing prosodic information to acoustic modeling (AM) for speech recognition is reported in this paper. It extends the conventional context-dependent (CD) triphone HMM modeling approach to further consider the dependency of phone model on the break type of nearby inter-syllable boundary. Four break types are considered, including major break, minor break, normal non-break, and tightly-coupled non-break. In the training phase, break labeling is automatically accomplished by a Prosody Labeling and Modeling algorithm proposed previously. Then, prosody-and phonetic-dependent phone models are constructed by a standard decision tree-based context clustering of HMMs. The effectiveness of the new AM was examined on a Mandarin syllable recognition task. Experimental results showed that the new approach outperformed the conventional CD-AM on achieving better syllable recognition rate as well as on obtaining a more efficient syllable lattice with better compromise on complexity verse syllable coverage rate.en_US
dc.language.isoen_USen_US
dc.subjectacoustic modelingen_US
dc.subjectspeech recognitionen_US
dc.subjectprosody-dependent acoustic modelen_US
dc.subjectprosodic breaken_US
dc.titleProsody-dependent Acoustic Modeling for Mandarin Speech Recognitionen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON SPEECH PROSODY, VOLS I AND IIen_US
dc.citation.spage139en_US
dc.citation.epage142en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000325160200035-
Appears in Collections:Conferences Paper