Summary of the paper

Title Comparing Speech and Text Classification on ICNALE
Authors 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.
Topics Document Classification, Text categorisation, Person Identification, Multilinguality
Full paper Comparing Speech and Text Classification on ICNALE
Bibtex @InProceedings{NISIOI16.1159,
  author = {Sergiu Nisioi},
  title = {Comparing Speech and Text Classification on ICNALE},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
Powered by ELDA © 2016 ELDA/ELRA