Stochastic language generation in dialogue using factored language models

Computational Linguistics

Volumn 40, Issue 4, 2014, Pages 763-799

  Mairesse, François ^a   Young, Steve ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; CROWDSOURCING; NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS; STOCHASTIC SYSTEMS;

AUTOMATED EVALUATION; DATA DRIVEN GENERATION; DATA-DRIVEN METHODS; HUMAN EVALUATION; LANGUAGE GENERATION; NATURAL LANGUAGE GENERATION; SEMANTIC CONCEPT; STATISTICAL MODELING;

STOCHASTIC MODELS;

EID: 84918491895     PISSN: 08912017     EISSN: 15309312     Source Type: Journal    
DOI: 10.1162/COLI_a_00199     Document Type: Article

References (53)

1. Angeli, Gabor, Percy Liang, and Dan Klein. 2010. A simple domain-independent probabilistic approach to generation. In Proceedings of EMNLP, pages 502–512, Cambridge, MA.
2. Bangalore, Srinivas and Owen Rambow. 2000. Exploiting a probabilistic hierarchical model for generation. In Proceedings of the 18th International Conference on Computational Linguistics (COLING), pages 42–48, Saarbrücken.
3. Bannard, Colin and Chris Callison-Burch. 2005. Paraphrasing with bilingual parallel corpora. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 597–604, Ann Arbor, MI.
4. Barzilay, Regina and Kathleen McKeown. 2001. Extracting paraphrases from a parallel corpus. In Proceedings of the 39th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 50–57, Toulouse.
5. Belz, Anja. 2008. Automatic generation of weather forecast texts using comprehensive probabilistic generation-space models. Natural Language Engineering, 14(4):431–455.
6. Bilmes, Jeff and Katrin Kirchhoff. 2003. Factored language models and generalized parallel backoff. In Proceedings of HLT-NAACL, Short Papers, pages 4–6, Edmonton.
7. Bulyko, Ivan and Mari Ostendorf. 2002. Efficient integrated response generation from multiple targets using weighted finite state transducers. Computer Speech and Language, 16(3-4):533–550.
8. Cahill, Aoife and Josef van Genabith. 2006. Robust PCFG-based generation using automatically acquired LFG approximations. In Proceedings of the 44th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 1033–1044, Sydney.
9. Chambers, Nathanael and James Allen. 2004. Stochastic language generation in a dialogue system: Toward a domain independent generator. In Proceedings 5th SIGdial Workshop on Discourse and Dialogue, pages 9–18, Cambridge,MA.
10. Collins, Michael. 2002a. Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithm. In Proceedings of EMNLP, pages 1–8, Philadelphia, PA.
11. Collins, Michael. 2002b. Ranking algorithms for named-entity extraction: Boosting and the voted perceptron. In Proceedings of the 40th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 489–496, Philadelphia, PA.
12. Collins, Michael and Brian Roark. 2004. Incremental parsing with the perceptron algorithm. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL), pages 111–118, Barcelona.
13. Espinosa, Dominic, Michael White, and Dennis Mehay. 2008. Hypertagging: Supertagging for surface realization with CCG. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL), pages 183–191, Columbus, OH.
14. Foster, Mary Ellen and Michael White. 2005. Assessing the impact of adaptive generation in the COMIC multimodal dialogue system. In Proceedings of the IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems, pages 24–31, Edinburgh.
15. He, Yulan and Steve Young. 2005. Semantic processing using the Hidden Vector State model. Computer Speech & Language, 19(1):85–106.
16. Isard, Amy, Carsten Brockmann, and Jon Oberlander. 2006. Individuality and alignment in generated dialogues. In Proceedings of INLG, pages 22–29, Sydney.
17. Kondadadi, Ravi, Blake Howald, and Frank Schilder. 2013. A statistical NLG framework for aggregated planning and realization. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL), pages 1406–1415, Sofia.
18. Konstas, Ioannis and Mirella Lapata. 2012. Concept-to-text generation via discriminative reranking. In Proceedings of the 50th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 369–378, Jeju Island.
19. Langkilde, Irene and Kevin Knight. 1998. Generation that exploits corpus-based statistical knowledge. In Proceedings of the 36th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 704–710, Montreal.
20. Langkilde-Geary, Irene. 2002. An empirical verification of coverage and correctness for a general-purpose sentence generator. In Proceedings of the International Conference on Natural Language Generation, pages 17–24, Harriman, NY.
21. Lavoie, Benoit and Owen Rambow. 1997. A fast and portable realizer for text generation systems. In Proceedings of the 3rd Conference on Applied Natural Language Processing, pages 265–268, Washington, DC.
22. Lefèvre, Fabrice. 2006. A DBN-based multi-level stochastic spoken language understanding system. In Proceedings of SLT, pages 78–81, Palm Beach, Aruba.
23. Lin, Dekang and Patrick Pantel. 2001. DIRT—discovery of inference rules from text. In Proceedings of ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pages 323–328, San Francisco, CA.
24. Lu, Wei, Hwee Tou Ng, and Wee Sun Lee. 2009. Natural language generation with tree conditional random fields. In Proceedings of EMNLP, pages 400–409, Edinburgh.
25. Mairesse, François, Milica Gašić, Filip Jurčíček, Simon Keizer, Blaise Thomson, Kai Yu, and Steve Young. 2010. Phrase-based statistical language generation using graphical models and active learning. In Proceedings of the 48th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 1552–1561, Uppsala.
26. Mairesse, François and Marilyn A.Walker. 2008. Trainable generation of Big-Five personality styles through data-driven parameter estimation. In Proceedings of the 46th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 165–173, Columbus, OH.
27. Mairesse, François and Marilyn A.Walker. 2011. Controlling user perceptions of linguistic style: Trainable generation of personality traits. Computational Linguistics, 37(3):455–488.
28. Mann, William C. and Sandra A. Thompson. 1988. Rhetorical structure theory. Toward a functional theory of text organization. Text, 8(3):243–281.
29. Nakanishi, Hiroko, Yusuke Miyao, and Jun’ichi Tsujii. 2005. Probabilistic methods for disambiguation of an HPSG-based chart generator. In Proceedings of the 9th InternationalWorkshop on Parsing Technology, pages 93–102, Vancouver.
30. Nakatsu, Crystal and Michael White. 2006. Learning to say it well: Reranking realizations by predicted synthesis quality. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), pages 1113–1120, Sydney.
31. Och, Franz Josef and Hermann Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1):19–51.
32. Oh, Alice H. and Alexander I. Rudnicky. 2002. Stochastic natural language generation for spoken dialog systems. Computer Speech and Language, 16:387–407.
33. Paiva, Daniel S. and Roger Evans. 2005. Empirically-based control of natural language generation. In Proceedings of the 43rd AnnualMeeting of the Association for Computational Linguistics (ACL), pages 58–65, Ann Arbor, MI.
34. Papineni, Kishore, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. BLEU: A method for automatic evaluation of machine translation. In Proceedings of the 40th AnnualMeeting of the Association for Computational Linguistics (ACL), pages 311–318, Philadelphia, PA.
35. Pon-Barry, Heather, Karl Schultz, Elizabeth Owen Bratt, Brady Clark, and Stanley Peters. 2006. Responding to student uncertainty in spoken tutorial dialogue systems. International Journal of Artificial Intelligence in Education, 16:171–194.
36. Rabiner, Lawrence R. 1989. Tutorial on HiddenMarkov Models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257–285.
37. Ratnaparkhi, Adwait. 2002. Trainable approaches to surface natural language generation and their application to conversational dialog systems. Computer Speech and Language, 16(3-4):435–455.
38. Reiter, Ehud and Anja Belz. 2009. An investigation into the validity of some metrics for automatically evaluating natural language generation systems. Computational Linguistics, 25:529–558.
39. Rieser, Verena and Oliver Lemon, 2010. Natural language generation as planning under uncertainty for spoken dialogue systems. In E. Krahmer & M. Theune, editors, Empirical Methods in Natural Language Generation, Springer, Heidelberg, pages 105–120.
40. Schatzmann, Jost, Blaise Thomson, Karl Weilhammer, Hui Ye, and Steve Young. 2007. Agenda-based user simulation for bootstrapping a POMDP dialogue system. In Proceedings of HLT-NAACL, Short Papers, pages 149–152, Rochester, NY.
41. Stent, Amanda and Martin Molina. 2009. Evaluating automatic extraction of rules for sentence plan construction. In Proceedings of the SIGdial Conference on Discourse and Dialogue, pages 290–297, London.
42. Stent, Amanda, Rashmi Prasad, and Marilyn A. Walker. 2004. Trainable sentence planning for complex information presentation in spoken dialog systems. In Proceedings of the 42nd AnnualMeeting of the Association for Computational Linguistics (ACL), pages 79–86, Barcelona.
43. Stone, Matthew, Doug DeCarlo, Insuk Oh, Christian Rodriguez, Adrian Stere, Alyssa Lees, and Chris Bregler. 2004. Speaking with hands: Creating animated conversational characters from recordings of human performance. In Proceedings of SIGGRAPH, pages 506–513, Los Angeles, CA.
44. Thomson, Blaise and Steve Young. 2010. Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems. Computer Speech & Language, 24(4):562–588.
45. Thomson, Blaise, Kai Yu, Simon Keizer, Milica Gašić, Filip Jurčíček, François Mairesse, and Steve Young. 2010. Bayesian dialogue system for the Let’s Go spoken dialogue challenge. In Proceedings of SLT, Special Session: The Spoken Dialogue Challenge, pages 460–465, Berkeley, CA.
46. Tokuda, Keiichi, Takayoshi Yoshimura, Takashi Masuko, Takao Kobayashi, and Tadashi Kitamura. 2000. Speech parameter generation algorithms for HMM-based speech synthesis. In Proceedings of ICASSP, pages 1315–1318, Istanbul.
47. Torrance, Nancy, Elizabeth Lee, and David R. Olson. 1992. The development of the distinction between paraphrase and exact wording in the recognition of utterances. In Proceedings of the AnnualMeeting of the American Educational Research Association, pages 1–11, San Francisco, CA. Tsochantaridis, Ioannis, Thomas Hofmann
48. Thorsten Joachims, and Yasemin Altun. 2004. Support vector learning for interdependent and structured output spaces. In Proceedings of ICML, pages 104–112, Bauff.
49. Varges, Sebastian and Chris Mellish. 2001. Instance-based natural language generation. In Proceedings of the Annual Meeting of the North American Chapter of the ACL (NAACL), pages 1–8, Pittsburgh, PA.
50. Walker, Marilyn A., Owen Rambow, and Monica Rogati. 2002. Training a sentence planner for spoken dialogue using boosting. Computer Speech and Language, 16(3-4):409–433.
51. White, Michael, Rajakrishnan Rajkumar, and Scott Martin. 2007. Towards broad coverage surface realization with CCG. In Proceedings of the Workshop on Using Corpora for NLG: Language Generation and Machine Translation, pages 22–30, Copenhagen.
52. Wong, Yuk Wah and Raymond J. Mooney. 2007. Generation by inverting a semantic parser that uses statistical machine translation. In Proceedings of HLT-NAACL, pages 172–179, Rochester, NY.
53. Young, Steve, Milica Gašić, Simon Keizer, François Mairesse, Jost Schatzmann, Blaise Thomson, and Kai Yu. 2010. The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management. Computer Speech and Language, 24(2):150–174.