Abstract
It would be useful to enable dialogue agents to project, through linguistic means, their individuality or personality. Equally, each member of a pair of agents ought to adjust its language (to a greater or lesser extent) to match that of its interlocutor. We describe CRAG, which generates dialogues between pairs of agents, who are linguistically distinguishable, but able to align. CRAG-2 makes use of OPENCCG and an over-generation and ranking approach, guided by a set of language models covering both personality and alignment. We illustrate with examples of output, and briefly note results from user studies with the earlier CRAG-1, indicating how CRAG-2 will be further evaluated. Related work is discussed, along with current limitations and future directions. © 2006 Association for Computational Linguistics.
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CITATION STYLE
Isard, A., Brockmann, C., & Oberlander, J. (2011). Individuality and alignment in generated dialogues. In COLING/ACL 2006: INLG-06 - 4th International Natural Language Generation Conference, Proceedings of the Conference (pp. 25–32). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1706269.1706277
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