Sentence planning for realtime navigational instructions
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
The first challenge on generating instructions in virtual environments
Empirical methods in natural language generation
Computational generation of referring expressions: A survey
Computational Linguistics
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Report on the second second challenge on generating instructions in virtual environments (GIVE-2.5)
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Report on the second second challenge on generating instructions in virtual environments (GIVE-2.5)
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Enhancing referential success by tracking hearer gaze
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
| Hi-index | 0.00 |
We present the Potsdam natural language generation systems P1 and P2 of the GIVE-2.5 Challenge. The systems implement two different referring expression generation models from Garoufi and Koller (2011) while behaving identically in all other respects. In particular, P1 combines symbolic and corpus-based methods for the generation of successful referring expressions, while P2 is based on a purely symbolic model which serves as a qualified baseline for comparison. We describe how the systems operated in the challenge and discuss the results, which indicate that P1 outperforms P2 in terms of several measures of referring expression success.