Automatic suprasegmental parameter extraction in learner corpora
In this chapter, an attempt is made to compute automatically suprasegmental – and, in particular, rhythmic – parameters that could be used to distinguish between a group of French learners of English and a group of native speakers. As a preliminary step, an automatic segmentation algorithm is benchmarked against manual segmentation. This assessment then leads us to reject the classic duration-based rhythm metrics and adopt alternative measurements involving pitch and intensity. Finally, we use an automatic classifier to check to what extent our metrics predict a reliable boundary between learner and native speech.
Cited by (2)
Cited by two other publications
Mairano, Paolo & Fabian Santiago
2020.
What vocabulary size tells us about pronunciation skills: Issues in assessing L2 learners.
Journal of French Language Studies 30:2
► pp. 141 ff.
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Park, Kwanghyun
2014.
Corpora and Language Assessment: The State of the Art.
Language Assessment Quarterly 11:1
► pp. 27 ff.
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