Abstract
This paper aims at improving the accuracy of user utterance understanding for an intelligent German-speaking wheelchair. We compare three different corpus-based context-free restriction grammars for its speech recognizer, which were tested for surface recognition and semantic feature extraction on a dedicated corpus of 135 utterances collected in an experiment with 13 participants. We show that grammars based on phonologically motivated units such as the foot and the syllable outperform phrase-structure grammars in complex scenarios where the extraction of a large number of semantic features is necessary.
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Vale, D.C., Mast, V. (2012). Using Foot-Syllable Grammars to Customize Speech Recognizers for Dialogue 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_72
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DOI: https://doi.org/10.1007/978-3-642-32790-2_72
Publisher Name: Springer, Berlin, Heidelberg
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