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1
Language Diversity: Speech Processing In A Multi-Lingual Context
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01843419 ; Annual Conference of the International Speech Communication Association , Haizhou Li, Helen Meng, Bin Ma, Eng Siong Chng, Lei Xie, Jan 2014, Singapore, Singapore (2014)
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2
Predicting Gradation of L2 English Mispronunciations using Crowdsourced Ratings and Phonological Rules
In: http://www1.se.cuhk.edu.hk/%7Ehccl/publications/pub/slate2013.pdf (2013)
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3
Predicting Gradation of L2 English Mispronunciations using Crowdsourced Ratings and Phonological Rules
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/2013_APSIPA.pdf (2013)
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4
The use of DBNHMMs for mispronunciation detection and diagnosis in L2 english to support computer-aided pronunciation training
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/xiaojun_interspeech2012.pdf (2012)
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Discriminatively trained acoustic models for improving mispronunciation detection and diagnosis in computer aided pronunciation training (CAPT
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/xiaojun_interspeech2010.pdf (2010)
Abstract: In this study, we propose a discriminative training algorithm to jointly minimize mispronunciation detection errors (i.e., false rejection and false acceptances) and diagnosis errors (i.e., correctly pinpointing mispronunciations but incorrectly stating how they are wrong). An optimization procedure, similar to Minimum Word Error (MWE) discriminative training, is developed to refine the ML-trained HMMs. The errors to be minimized are obtained by comparing transcribed training utterances (including mispronunciations) with Extended Recognition Networks [3] which contain both canonical pronunciations and explicitly modeled mispronunciations. The ERN is compiled by handcrafted rules, or data-driven rules. Several conclusions can be drawn from the experiments: (1) data-driven rules are more effective than hand-crafted ones in capturing mispronunciations; (2) compared with the ML training baseline, discriminative training can reduce false rejections and diagnostic errors, though false acceptances increase slightly due to a small number of false-acceptance samples in the training set. Index Terms: CAPT, mispronunciation detection and diagnosis, discriminative training, data-driven phonological rule extraction
URL: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/xiaojun_interspeech2010.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.1303
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Automatic Derivation of Phonological Rules for Mispronunciation Detection in a Computer-Assisted Pronunciation Training System
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/Lo_INTERSPEECH2010_20100710.pdf (2010)
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7
Development of an articulatory visual-speech synthesizer to support language learning
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/ISCSLP2010-20100924.pdf (2010)
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8
Automatic story segmentation using a Bayesian decision framework for statistical models of lexical chain features
In: http://www1.se.cuhk.edu.hk/%7Ehccl/publications/pub/Lo_ACL-IJCNLP2009.pdf (2009)
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9
Developing a ComputerAided Pronunciation System for Chinese-Speaking Learners of English
In: http://www1.se.cuhk.edu.hk/%7Ehccl/publications/pub/W020091216352469032128.pdf (2009)
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10
Studying L2 suprasegmental features in Asian Englishes: a position paper
In: http://www.ling.sinica.edu.tw/eip/files/publish/2009.9.17.7807558.69687253.pdf (2009)
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11
Deriving salient learners’ mispronunciations from cross-language phonological comparisons
In: http://www.se.cuhk.edu.hk/hccl/publications/pub/Meng-ASRU2007.5.pdf (2007)
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12
Initial Experiments on Automatic Story Segmentation
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/Initial Experiments on Automatic Story Segmentation in Chinese Spoken Documents Using Lexical Cohesion of Extracted Named Entities.pdf (2006)
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13
et.al, "The Multi-biometric, Multi-device and Multilingual (M3) Corpus
In: http://www.se.cuhk.edu.hk/~wklo/docpub/MengMMUA2006.pdf (2006)
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14
Design and Development of a Bilingual Reading Comprehension Corpus
In: http://www.se.cuhk.edu.hk/hccl/publications/pub/BRCC.pdf (2005)
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15
Isis: An Adaptive, Trilingual Conversational System with Interleaving Interaction and Delegation Dialogs
In: http://www.se.cuhk.edu.hk/hccl/publications/pub/p268-meng.pdf (2004)
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16
A two-level schema for detecting recognition errors
In: http://www.se.cuhk.edu.hk/hccl/publications/pub/Zhou_ICSLP2004.pdf (2004)
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17
English-Chinese bilingual textindependent speaker verification
In: http://www1.se.cuhk.edu.hk/~hccl/publications/pub/icassp2004_Ma.pdf (2004)
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18
Multi-scale audio indexing for translingual spoken document retrieval
In: http://www.se.cuhk.edu.hk/~wklo/docpub/WangICASSP2001.pdf (2001)
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19
Multi-Scale Audio Indexing For Translingual Spoken Document Retrieval
In: http://www.se.cuhk.edu.hk/PEOPLE/hmmeng/Meng_AudioIndex_ICASSP2001.pdf (2001)
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20
Discovery of Unknown Events From Multi-lingual News
In: http://www.se.cuhk.edu.hk/PEOPLE/hmmeng/ICCPOL2001.ps.gz (2001)
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