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The effectiveness of computer-based speech corrective feedback for improving segmental quality in L2 Dutch

Published online by Cambridge University Press:  28 March 2008

Ambra Neri
Affiliation:
Centre for Speech and Language Technology, Department of Linguistics, Radboud University Nijmegen, Erasmusplein 1, 6525 HT Nijmegen, The Netherlands (email: C.Cucchiarini@let.ru.nl; ambra.neri@gmail.com; strik@let.ru.nl)
Catia Cucchiarini
Affiliation:
Centre for Speech and Language Technology, Department of Linguistics, Radboud University Nijmegen, Erasmusplein 1, 6525 HT Nijmegen, The Netherlands (email: C.Cucchiarini@let.ru.nl; ambra.neri@gmail.com; strik@let.ru.nl)
Helmer Strik
Affiliation:
Centre for Speech and Language Technology, Department of Linguistics, Radboud University Nijmegen, Erasmusplein 1, 6525 HT Nijmegen, The Netherlands (email: C.Cucchiarini@let.ru.nl; ambra.neri@gmail.com; strik@let.ru.nl)
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Abstract

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Although the success of automatic speech recognition (ASR)-based Computer Assisted Pronunciation Training (CAPT) systems is increasing, little is known about the pedagogical effectiveness of these systems. This is particularly regrettable because ASR technology still suffers from limitations that may result in the provision of erroneous feedback, possibly leading to learning breakdowns. To study the effectiveness of ASR-based feedback for improving pronunciation, we developed and tested a CAPT system providing automatic feedback on Dutch phonemes that are problematic for adult learners of Dutch. Thirty immigrants who were studying Dutch were assigned to three groups using either the ASR-based CAPT system with automatic feedback, a CAPT system without feedback, or no CAPT system. Pronunciation quality was assessed for each participant before and after the training by human experts who evaluated overall segmental quality and the quality of the phonemes addressed in the training. The participants' impressions of the CAPT system used were also studied through anonymous questionnaires. The results on global segmental quality show that the group receiving ASR-based feedback made the largest mean improvement, but the groups' mean improvements did not differ significantly. The group receiving ASR-based feedback showed a significantly larger improvement than the no-feedback group in the segmental quality of the problematic phonemes targeted.

Type
Research Article
Copyright
Copyright © European Association for Computer Assisted Language Learning 2008