Automatic pronunciation error detection in non-native speech : the case of vowel errors in Dutch
| Autor: | Catia Cucchiarini, Joost van Doremalen, Helmer Strik |
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| Rok vydání: | 2013 |
| Předmět: |
Male
Acoustics and Ultrasonics Voice Quality Computer science Speech recognition Realization (linguistics) Word error rate Multilingualism Pronunciation Speech Acoustics Pattern Recognition Automated Language and Speech Learning and Therapy Speech Production Measurement Arts and Humanities (miscellaneous) Phonetics Vowel Humans Learning GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) Automation Laboratory Signal Processing Computer-Assisted Acoustics Speech processing Linguistics Language in Society Metric (mathematics) Regression Analysis Female Algorithms |
| Zdroj: | The Journal of the Acoustical Society of America, 134, 1336-1347 The Journal of the Acoustical Society of America, 134, 2, pp. 1336-1347 |
| ISSN: | 0001-4966 |
| Popis: | This research is aimed at analyzing and improving automatic pronunciation error detection in a second language. Dutch vowels spoken by adult non-native learners of Dutch are used as a test case. A first study on Dutch pronunciation by L2 learners with different L1s revealed that vowel pronunciation errors are relatively frequent and often concern subtle acoustic differences between the realization and the target sound. In a second study automatic pronunciation error detection experiments were conducted to compare existing measures to a metric that takes account of the error patterns observed to capture relevant acoustic differences. The results of the two studies do indeed show that error patterns bear information that can be usefully employed in weighted automatic measures of pronunciation quality. In addition, it appears that combining such a weighted metric with existing measures improves the equal error rate by 6.1 percentage points from 0.297, for the Goodness of Pronunciation (GOP) algorithm, to 0.236. |
| Databáze: | OpenAIRE |
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