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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Discrimination between pathological and normal voices using GMM-SVM approach Zhang, Jianping; Wang, Xiang; Yan, Yonghong In: Journal of voice. - Amsterdam [u.a.] : Elsevier 25 (2011) 1, 38-43 BLLDB OLC Linguistik Show details 2 Comparative intelligibility investigation of single-channel noise-reduction algorithms for Chinese, Japanese, and Englisha Li, Junfeng; Yang, Lin; Zhang, Jianping. - : Acoustical Society of America, 2011 BASE Show details 3 Chinese Scientific Educational Film Creation: The Return of the Film Nature HE, Hongchi; ZHANG, Jianping In: Cross-Cultural Communication; Vol 7, No 2 (2011): Cross-cultural Communication; 260-264 ; 1923-6700 ; 1712-8358 (2011) BASE Show details 4 Some current issues of streaming data mining Zhang, Jianping; Liu, Huan; Wang, Paul P. In: Information sciences. - New York, NY : Elsevier Science Inc. 176 (2006) 14, 1949-1951 OLC Linguistik Show details 5 What kind of pronunciation variation is hard for triphones to model Dan Jurafsky; Wayne Ward; Zhang Jianping... In: http://www.colorado.edu/linguistics/jurafsky/icassp01.pdf (2001) BASE Show details 6 What Kind Of Pronunciation Variation Is Hard For Triphones To Model? Dan Jurafsky; Wayne Ward; Zhang Jianping; Keith Herold; Yu Xiuyang; Zhang Sen In: http://www.colorado.edu/linguistics/jurafsky/icassp01.ps (2001) Abstract: In order to help understand why gains in pronunciation modeling have proven so elusive, we investigated which kinds of pronunciation variation are well captured by triphone models, and which are not. We do this by examining the change in behavior of a recognizer as it receives further triphone training. We show that many of the kinds of variation which previous pronunciation models attempt to capture, including phone substitution or phone reduction, are in fact already well captured by triphones. Our analysis suggests new areas where future pronunciation models should focus, including syllable deletion. 1. INTRODUCTION Many studies of human-to-human speech have shown that pronunciation variation is a key factor contributing to the high error rates of current recognizers. For example [1] showed that Switchboard word error decreased from 40% to 8% if the dictionary pronunciation matched the actual pronunciation. While the need for better pronunciation modeling is widely acknowledged, . URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.26.9608 http://www.colorado.edu/linguistics/jurafsky/icassp01.ps BASE Hide details 7 WHAT KIND OF PRONUNCIATION VARIATION IS HARD FOR TRIPHONES TO MODEL? Dan Jurafsky; Wayne Ward; Zhang Jianping... In: http://www.ling.ohio-state.edu/~kyoon/pdf/PAPER-General-Exam/pronunciation-variation-hard-for-triphones-to-model-Jurafsky-ICASSP01.pdf (2001) BASE Show details 8 The equivalence between two definitions of digital surfaces Chen, Li; Cooley, Donald H.; Zhang, Jianping In: Information sciences. - New York, NY : Elsevier Science Inc. 115 (1999) 1-4, 201-220 OLC Linguistik Show details

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