- 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.
- Links To Paper
- 1st Link
- Bibtex format
- @InProceedings{EDI-INF-RR-0974,
- author = {
Amy Isard
and Carsten Brockmann
and Jon Oberlander
},
- title = {Individuality and Alignment in Generated Dialogues},
- book title = {Proceedings of the Fourth International Natural Language Generation Conference},
- publisher = {Association for Computational Linguistics},
- year = 2006,
- month = {Jul},
- pages = {25-32},
- url = {http://www.aclweb.org/anthology/W/W06/W06-1405},
- }
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