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Automatic Pronunciation Error Detection and Feedback Generation for CALL Applications

  • Renlong AiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9192)

Abstract

This paper describes a new method of automatic error detection in Computer Assisted Language Learning (CAPT) system. The method combines linguistic knowledge and modern speech technology. Our HMM classifier trained from annotations of linguists is not only capable of classifying correct and wrong phonemes, but also can tell how wrong an error phoneme is pronounced. Phone errors in L2’s speech, like phoneme substitution or distortion are detected with high accuracy, and at the same time, corrective feedback with multimedia support, which demonstrates how exactly error phonemes should be pronounced, is also generated.

Keywords

L2 pronunciation errors Automatic error detection Feedback 

Notes

Acknowledgement

This research was partially supported by the German Federal Ministry of Education and Research (BMBF) through the project Sprinter (contract 01IS12006A), Deependance (contract 01IW11003) and All Sides (contract 01IW14002).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.DFKI GmbH, Language Technology LabBerlinGermany

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