Comparing different approaches for automatic pronunciation error detection

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Strik, Helmer and Truong, Khiet and Wet, Febe de and Cucchiarini, Catia (2009) Comparing different approaches for automatic pronunciation error detection. Speech Communication, 51 (10). pp. 845-852. ISSN 0167-6393

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Abstract:One of the biggest challenges in designing computer assisted language learning (CALL) applications that provide automatic feedback on pronunciation errors consists in reliably detecting the pronunciation errors at such a detailed level that the information provided can be useful to learners. In our research we investigate pronunciation errors frequently made by foreigners learning Dutch as a second language. In the present paper we focus on the velar fricative /x/ and the velar plosive /k/. We compare four types of classifiers that can be used to detect erroneous pronunciations of these phones: two acoustic–phonetic classifiers (one of which employs Linear Discriminant Analysis (LDA)), a classifier based on cepstral coefficients in combination with LDA, and one based on confidence measures (the so-called Goodness Of Pronunciation score). The best results were obtained for the two LDA classifiers which produced accuracy levels of about 85–93%.
Item Type:Article
Copyright:© 2009 Elsevier
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/79841
Official URL:http://dx.doi.org/10.1016/j.specom.2009.05.007
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