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Lexical stress detection for L2 English speech using deep belief networks.

, , , and . INTERSPEECH, page 1811-1815. ISCA, (2013)

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Rendering a personalized photo-real talking head from short video footage., , , and . ISCSLP, page 129-134. IEEE, (2010)N-gram Fragment Sequence Based Unsupervised Domain-Specific Document Readability., , and . COLING, page 1309-1326. Indian Institute of Technology Bombay, (2012)Capturing L2 segmental mispronunciations with joint-sequence models in Computer-Aided Pronunciation Training (CAPT)., , and . ISCSLP, page 84-88. IEEE, (2010)On Mispronunciation Lexicon Generation Using Joint-Sequence Multigrams in Computer-Aided Pronunciation Training (CAPT)., , and . INTERSPEECH, page 865-868. ISCA, (2011)Implementation of an extended recognition network for mispronunciation detection and diagnosis in computer-assisted pronunciation training., , , and . SLaTE, page 45-48. ISCA, (2009)Predicting gradation of L2 English mispronunciations using crowdsourced ratings and phonological rules., , and . SLaTE, page 127-131. ISCA, (2013)Discriminative acoustic model for improving mispronunciation detection and diagnosis in computer-aided pronunciation training (CAPT)., , and . INTERSPEECH, page 757-760. ISCA, (2010)A two-pass framework of mispronunciation detection & diagnosis for computer-aided pronunciation training., , and . APSIPA, page 384-387. IEEE, (2015)HMM-based motion trajectory generation for speech animation synthesis., , , and . AVSP, page 170. ISCA, (2009)Deep Learning for Acoustic Modeling in Parametric Speech Generation: A systematic review of existing techniques and future trends., , , , , , , and . IEEE Signal Process. Mag., 32 (3): 35-52 (2015)