Natural language generator for spoken dialogue systems with a statistical sentence planner
TGen is a natural language generator, composed of:
- a statistical sentence planner based on A*-style search, with a candidate plan generator and a perceptron ranker
- a rule-based surface realizer using the existing Treex NLP toolkit
TGen can be trained from pairs of source meaning representations (dialogue acts) and target sentences. More details can be found in our ACL 2015 paper.
TGen is currently highly experimental and not very well tested. Use at your own risk.
To get the version used in our ACL 2015 paper, see this release. The current master version has new experimental features using neural networks (not stable and worse performance than perceptron).
For TGen to work properly, you need to have these modules installed:
The first two ones can be avoided by just copying a few libraries; these will be integrated here in the future.
Please cite this paper when using parts of TGen in your work:
Ondřej Dušek and Filip Jurčíček (2015): Training a Natural Language Generator From Unaligned Data. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, pages 451–461, Beijing, China.
Author: Ondřej Dušek
Copyright © 2014-2015 Institute of Formal and Applied Linguistics, Charles University in Prague.
Licensed under the Apache License, Version 2.0.
Work on this project was funded by the Ministry of Education, Youth and Sports of the Czech Republic under the grant agreement LK11221 and core research funding, SVV project 260 104, and GAUK grant 2058214 of Charles University in Prague. It used language resources stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2010013).