Comparing Speech and Text Classification on ICNALE

Sergiu Nisioi


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.
Anthology ID:
L16-1542
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3402–3406
Language:
URL:
https://aclanthology.org/L16-1542
DOI:
Bibkey:
Cite (ACL):
Sergiu Nisioi. 2016. Comparing Speech and Text Classification on ICNALE. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3402–3406, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Comparing Speech and Text Classification on ICNALE (Nisioi, LREC 2016)
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PDF:
https://aclanthology.org/L16-1542.pdf