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Conference Paper: Computer aided evaluation of intonation for language learning based on prosodic unit segmentation

TitleComputer aided evaluation of intonation for language learning based on prosodic unit segmentation
Authors
KeywordsFoot
Intonation
Prosodic Unit
Prosody
Segmentation
Issue Date2010
Citation
Apsipa Asc 2010 - Asia-Pacific Signal And Information Processing Association Annual Summit And Conference, 2010, p. 788-793 How to Cite?
AbstractThis paper considers computer aided intonation evaluation based on prosodic unit segmentation for the learning of English. To evaluate the intonation of utterances of a foreign English learner, the learner's intonation pattern is normally compared with that of the teacher's utterance. The evaluation score can be obtained by measuring the "distance" between the two intonation patterns. One salient feature of most current computer-aided language learning (CALL) systems is segmentation of an utterance according to word or syllable boundaries for distance measurement in the evaluation process. This method may lead to inaccuracy of the evaluation, since the prosody of natural speech always corresponds to the boundaries of prosodic units, such as foot and intonation unit, rather than the word boundaries in an utterance. In this paper, the pronounced sentences are segmented according to prosodic unit boundaries. Dynamic Time Warping (DTW) and Mahalanobis Distance are then used to measure the difference between the learner's and the teacher's intonation, leading to a machine score.
Persistent Identifierhttp://hdl.handle.net/10722/159071
References

 

DC FieldValueLanguage
dc.contributor.authorZhao, Sen_US
dc.contributor.authorLuke, KKen_US
dc.contributor.authorKoh, SNen_US
dc.contributor.authorZhang, Yen_US
dc.date.accessioned2012-08-08T09:06:28Z-
dc.date.available2012-08-08T09:06:28Z-
dc.date.issued2010en_US
dc.identifier.citationApsipa Asc 2010 - Asia-Pacific Signal And Information Processing Association Annual Summit And Conference, 2010, p. 788-793en_US
dc.identifier.urihttp://hdl.handle.net/10722/159071-
dc.description.abstractThis paper considers computer aided intonation evaluation based on prosodic unit segmentation for the learning of English. To evaluate the intonation of utterances of a foreign English learner, the learner's intonation pattern is normally compared with that of the teacher's utterance. The evaluation score can be obtained by measuring the "distance" between the two intonation patterns. One salient feature of most current computer-aided language learning (CALL) systems is segmentation of an utterance according to word or syllable boundaries for distance measurement in the evaluation process. This method may lead to inaccuracy of the evaluation, since the prosody of natural speech always corresponds to the boundaries of prosodic units, such as foot and intonation unit, rather than the word boundaries in an utterance. In this paper, the pronounced sentences are segmented according to prosodic unit boundaries. Dynamic Time Warping (DTW) and Mahalanobis Distance are then used to measure the difference between the learner's and the teacher's intonation, leading to a machine score.en_US
dc.languageengen_US
dc.relation.ispartofAPSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conferenceen_US
dc.subjectFooten_US
dc.subjectIntonationen_US
dc.subjectProsodic Uniten_US
dc.subjectProsodyen_US
dc.subjectSegmentationen_US
dc.titleComputer aided evaluation of intonation for language learning based on prosodic unit segmentationen_US
dc.typeConference_Paperen_US
dc.identifier.emailLuke, KK:kkluke@hkusua.hku.hken_US
dc.identifier.authorityLuke, KK=rp01201en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-79958092567en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79958092567&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage788en_US
dc.identifier.epage793en_US
dc.identifier.scopusauthoridZhao, S=41462178800en_US
dc.identifier.scopusauthoridLuke, KK=7003697439en_US
dc.identifier.scopusauthoridKoh, SN=7202062508en_US
dc.identifier.scopusauthoridZhang, Y=41462220900en_US

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