Publication

Automatically identifying characteristic features of non-native English accents

Bloem, J., Wieling, M. & Nerbonne, J., 2016, The Future of Dialects: selected papers from Methods in Dialectology XV. Côté, M-H., Knooihuizen, R. & Nerbonne, J. (eds.). Language Science Press, p. 155-172

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

In this work, we demonstrate the application of statistical measures from dialectometry to the study of accented English speech. This new methodology enables a more quantitative approach to the study of accents. Studies on spoken dialect data have shown that a combination of representativeness (the difference between pronunciations within the language variety is small) and distinctiveness (the difference between pronunciations inside and outside the variety is large) is a good way to identify characteristic features of a language variety. We applied this method from dialectology to transcriptions of the words from the Speech Accent Archive, while treating L2 English speakers with different L1s as ‘varieties’. This yields lists of words that are pronounced characteristically differently in comparison to native accents of English. We discuss English accent characteristics for French, Hungarian and Dutch. We compare the French and Hungarian results to phonological descriptions of those languages to identify the source of the difference. The Dutch results are compared to a Dutch accents judgement study (Van den Doel 2006) to evaluate the measure. Knowing about these characteristic features of accents has useful applicationsin teaching L2 learners of English, since potentially difficult sounds or sound combinations can be identified and addressed based on the learner’s native language.
Original languageEnglish
Title of host publicationThe Future of Dialects
Subtitle of host publicationselected papers from Methods in Dialectology XV
EditorsMarie-Hélène Côté, Remco Knooihuizen, John Nerbonne
PublisherLanguage Science Press
Pages155-172
ISBN (Print)9783946234197
Publication statusPublished - 2016

ID: 23254568