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.
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© 2012 Springer-Verlag Berlin Heidelberg
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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
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DOI: https://doi.org/10.1007/978-3-642-32790-2_75
Publisher Name: Springer, Berlin, Heidelberg
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