Towards automatic tone correction in non-native mandarin

Authors:
Mitchell Peabody;Stephanie Seneff
Affiliations:
Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA;Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA
Venue:
ISCSLP'06 Proceedings of the 5th international conference on Chinese Spoken Language Processing
Year:
2006

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ISCSLP'06 Proceedings of the 5th international conference on Chinese Spoken Language Processing

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Abstract

Feedback is an important part of foreign language learning and Computer Aided Language Learning (CALL) systems. For pronunciation tutoring, one method to provide feedback is to provide examples of correct speech for the student to imitate. However, this may be frustrating if a student is unable to completely match the example speech. This research advances towards providing feedback using a student’s own voice. Using the case of an American learning Mandarin Chinese, the differences between native and non-native pronunciations of Mandarin tone are highlighted, and a method for correcting tone errors is presented, which uses pitch transformation techniques to alter student tone productions while maintaining other voice characteristics.