Bootstrapping Syntax and Recursion using Alginment-Based Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Referring expression generation through attribute-based heuristics
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Noun phrase generation for situated dialogs
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
A linguistic ontology of space for natural language processing
Artificial Intelligence
Automated planning for situated natural language generation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Generating referring expressions with reference domain theory
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
The first challenge on generating instructions in virtual environments
Empirical methods in natural language generation
Spatially-aware dialogue control using hierarchical reinforcement learning
ACM Transactions on Speech and Language Processing (TSLP)
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Giving instructions in virtual environments by corpus based selection
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Optimising natural language generation decision making for situated dialogue
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
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
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This paper presents the Bremen system for the GIVE-2.5 challenge. It is based on decision trees learnt from new annotations of the GIVE corpus augmented with manually specified rules. Surface realisation is based on context-free grammars. The paper will address advantages and shortcomings of the approach and discuss how the present system can serve as a baseline for a future evaluation with an improved version using hierarchical reinforcement learning with graphical models.