Abstract
In this work, we present an approach to language understanding using corpus-based and statistical language models based on multigrams. Assuming that we can assign meanings to segments of words, the n-multigram modelization is a good approach to model sequences of segments that have semantic information associated to them. This approach has been applied to the task of speech understanding in the framework of a dialogue system that answers queries about train timetables in Spanish. Some experimental results are also reported.
Work partially funded by CICYT under project TIC2002-04103-C03-03, Spain.
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Hurtado, L., Segarra, E., García, F., Sanchis, E. (2004). Language Understanding Using n-multigram Models. In: Vicedo, J.L., Martínez-Barco, P., Muńoz, R., Saiz Noeda, M. (eds) Advances in Natural Language Processing. EsTAL 2004. Lecture Notes in Computer Science(), vol 3230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30228-5_19
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DOI: https://doi.org/10.1007/978-3-540-30228-5_19
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