The long term goal of this research is to build artificial conversational intelligence that can set up or participate in the fluent conversational interactions as good as people in order to benefit each other. This paper discusses conversation quanta as a foundation of conversational intelligence. In contrast to conversational systems for which much emphasis has been placed on the symbolic processing and algorithms, our approach is data-intensive, allowing for the conversational system to acquire the depth and proficiency in interaction in an incremental fashion, in addition to the broad coverage and robustness. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Nishida, T. (2013). Conversation Quantization as a Foundation of Conversational Intelligence. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7813 LNCS, pp. 230–245). Springer Verlag. https://doi.org/10.1007/978-3-642-37134-9_18
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