Nikos Engonopoulos


pdf bib
Discovering User Groups for Natural Language Generation
Nikos Engonopoulos | Christoph Teichmann | Alexander Koller
Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue

We present a model which predicts how individual users of a dialog system understand and produce utterances based on user groups. In contrast to previous work, these user groups are not specified beforehand, but learned in training. We evaluate on two referring expression (RE) generation tasks; our experiments show that our model can identify user groups and learn how to most effectively talk to them, and can dynamically assign unseen users to the correct groups as they interact with the system.


pdf bib
Integrated sentence generation using charts
Alexander Koller | Nikos Engonopoulos
Proceedings of the 10th International Conference on Natural Language Generation

Integrating surface realization and the generation of referring expressions into a single algorithm can improve the quality of the generated sentences. Existing algorithms for doing this, such as SPUD and CRISP, are search-based and can be slow or incomplete. We offer a chart-based algorithm for integrated sentence generation and demonstrate its runtime efficiency.


pdf bib
Predicting the Resolution of Referring Expressions from User Behavior
Nikos Engonopoulos | Martín Villalba | Ivan Titov | Alexander Koller
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing


pdf bib
A Comparison of Knowledge-based Algorithms for Graded Word Sense Assignment
Annemarie Friedrich | Nikos Engonopoulos | Stefan Thater | Manfred Pinkal
Proceedings of COLING 2012: Posters