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ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)Venice, Italy |
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Computer Assisted Pronunciation Training (CAPT) is
becoming more and more popular among language learners.
Most effective CAPT systems take advantage of the learners
L1 and cater exercises and feedback specific to the language
transfer effects. This paper presents a statistical machine
translation (MT) based approach to model salient phonological
errors present in an L1 population. The output of the MT
system is coupled with a speech recognition system to detect
non-native phonological errors. On a Korean learners of
English corpus, the MT approach shows a 32.9% relative
improvement in phone error detection and a 49% relative
improvement in phone error identification compared to edit
distance based modeling techniques. Similar performance
improvements were observed on Japanese learners of English
corpus.
Index Terms. phonological error modeling, machine
translation, speech recognition
Bibliographic reference. Stanley, Theban / Hacioglu, Kadri / Pellom, Bryan (2011): "Statistical machine translation framework for modeling phonological errors in computer assisted pronunciation training system", In SLaTE-2011, 125-128.