Abstract
Computer Assisted Language Learning (CALL) systems are one of the key technologies in assisting learners to master a second language. The progress in automatic speech recognition has advanced research on CALL systems that recognize speech constructed by students. Reliable recognition is still difficult from speech by second language speakers, which contains pronunciation, lexical, and grammatical errors. We developed a dialogue-based CALL system using a learner corpus. The system uses two kinds of automatic speech recognizers using ngram and finite state automaton (FSA). We also propose a classification method for classifying the speech recognition results from the recognizer using FSA as accepted or rejected. The classification method uses the differences in acoustic likelihoods of both recognizers as well as the edit distance between strings of output words from both recognizers and coverage estimation by FSA over various expressions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Eskenazi, M.: Using Automatic Speech Processing for Foreign Language Pronunciation Tutoring: Some Issues and Prototype. Language Learning and Technology 2(2), 62–76 (1999)
Kweon, O., Ito, A., Suzuki, M., Makino, S.: A grammatical error detection method for dialogue-based CALL system. J. Natural Language Processing 12(4), 137–156 (2005)
Nakamura, S., et al.: The ATR Multilingual Speech-to-Speech Translation System. IEEE Trans. ASLP 14(2), 365–376 (2006)
Minematsu, N., Nishina, K., Nakagawa, S.: Readspeech database for foreign language learning. JASJ 59(6), 345–350 (2003) (in Japanese)
Takami, J., Sagayama, S.: A successive state splitting algorithm for efficient allophone modeling. In: Proc. ICASSP, vol. 1, pp. 573–576 (1992)
Takezawa, T., Sumita, E., Sugaya, F., Yamamoto, H., Yamamoto, S.: Toward a broad-coverage bilingual corpus for speech translation of travel conversations in the real world. In: Proc. LREC, 27–2, pp. 147–152 (2002)
Yasuda, K., Kitamura, K., Yamamoto, S., Masuzo, Y.: Development and Applications of an English Learner Corpus with Multiple Information Tags. J. of NLP 16(4), 47–63 (2009) (in Japanese)
Watanabe, T., Tsukada, S.: Unknown Utterance Rejection Using Likelihood Normalization Based on Syllable Recognition. IEICE Trans. 75-D2(12), 2002–2009 (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nagai, Y., Senzai, T., Yamamoto, S., Nishida, M. (2012). Sentence Classification with Grammatical Errors and Those Out of Scope of Grammar Assumption for Dialogue-Based CALL Systems. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_75
Download citation
DOI: https://doi.org/10.1007/978-3-642-32790-2_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32789-6
Online ISBN: 978-3-642-32790-2
eBook Packages: Computer ScienceComputer Science (R0)