Paper: Conditional Random Fields for Responsive Surface Realisation using Global Features

ACL ID P13-1123
Title Conditional Random Fields for Responsive Surface Realisation using Global Features
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Surface realisers in spoken dialogue sys- tems need to be more responsive than con- ventional surface realisers. They need to be sensitive to the utterance context as well as robust to partial or changing generator inputs. We formulate surface realisation as a sequence labelling task and combine the use of conditional random fields (CRFs) with semantic trees. Due to their extended notion of context, CRFs are able to take the global utterance context into account and are less constrained by local features than other realisers. This leads to more natural and less repetitive surface realisa- tion. It also allows generation from partial and modified inputs and is therefore ap- plicable to incremental surface realisation. Results from a human rating study confirm that users are sensitive to thi...