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Comparing Speech and Text Classification on ICNALE
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)
Abstract
In this paper we explore and compare a speech and text classification approach on a corpus of native and non-native English speakers. We experiment on a subset of the International Corpus Network of Asian Learners of English containing the recorded speeches and the equivalent text transcriptions. Our results suggest a high correlation between the spoken and written classification results, showing that native accent is highly correlated with grammatical structures found in text.