Abstract
In order to build dialogue systems to tackle the ambitious task of holding social conversations, we argue that we need a data-driven approach that includes insight into human conversational “chit-chat”, and which incorporates different natural language processing modules. Our strategy is to analyze and index large corpora of social media data, including Twitter conversations, online debates, dialogues between friends, and blog posts, and then to couple this data retrieval with modules that perform tasks such as sentiment and style analysis, topic modeling, and summarization. We aim for personal assistants that can learn more nuanced human language, and to grow from task-oriented agents to more personable social bots.
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References
Amazon Echo. https://www.amazon.com/Amazon-Echo-Bluetooth-Speaker-with-WiFi-Alexa/dp/B00X4WHP5E
Bowden KK, Lin GI, Reed LI, Tree JEF, Walker MA (2016) M2D: monolog to dialog generation for conversational story telling. In: Interactive storytelling—9th international conference on interactive digital storytelling, ICIDS 2016, Los Angeles, CA, USA, November 15–18, 2016, Proceedings, pp 12–24
Bowden KK, Oraby S, Wu J, Misra A, Walker M (2017) Combining search with structured data to create a more engaging user experience in open domain dialogue. SCAI 2017
Bowden KK, Wu J, Oraby S, Misra A, Walker M (2017) Slugbot: an application of a novel and scalable open domain socialbot framework. In: Alexa prize proceedings
Google Home Features. https://madeby.google.com/home/features/
Henderson M, Thomson B, Williams J (2014) The second dialog state tracking challenge. In: Proceedings of SIGDIAL. ACL association for computational linguistics. https://www.microsoft.com/en-us/research/publication/the-second-dialog-state-tracking-challenge/
Higashinaka R, Imamura K, Meguro T, Miyazaki C, Kobayashi N, Sugiyama H, Hirano T, Makino T, Matsuo Y (2014) Towards an open-domain conversational system fully based on natural language processing. In: COLING. ACL
Hirschman L (2000) Evaluating spoken language interaction: experiences from the darpa spoken language program 1990–1995. MIT Press, Cambridge, Mass, Spoken Language Discourse
Kadlec R, Schmid M, Kleindienst J (2015) Improved deep learning baselines for ubuntu corpus dialogs. CoRR abs/1510.03753. http://arxiv.org/abs/1510.03753
Li J, Galley M, Brockett C, Gao J, Dolan B (2016) A persona-based neural conversation model. arXiv preprint http://arxiv.org/abs/1603.06155
Lowe RT, Pow N, Serban IV, Charlin L, Liu C, Pineau J (2017) Training end-to-end dialogue systems with the ubuntu dialogue corpus. D&D 8(1): 31–65. http://dad.uni-bielefeld.de/index.php/dad/article/view/3698
Lowe R, Pow N, Serban I, Pineau J (2015) The ubuntu dialogue corpus: a large dataset for research in unstructured multi-turn dialogue systems. In: Proceedings of the SIGDIAL 2015 conference, the 16th annual meeting of the special interest group on discourse and dialogue, 2–4 September 2015, Prague, Czech Republic, pp 285–294. http://aclweb.org/anthology/W/W15/W15-4640.pdf
Lukin S, Ryan JO, Walker MA (2014) Automating direct speech variations in stories and games. In: Proceedings of the 3rd workshop on games and NLP
Misra A, Anand P, Tree JEF, Walker MA (2015) Using summarization to discover argument facets in online idealogical dialog. In: NAACL HLT 2015, The 2015 conference of the north american chapter of the association for computational linguistics: human language technologies, Denver, Colorado, USA, May 31 - June 5, 2015. http://aclweb.org/anthology/N/N15/N15-1046.pdf
Misra A, Ecker B, Walker MA (2016) Measuring the similarity of sentential arguments in dialogue. In: Proceedings of the SIGDIAL 2016 conference, the 17th annual meeting of the special interest group on discourse and dialogue, 13–15 September 2016, Los Angeles, CA, USA. http://aclweb.org/anthology/W/W16/W16-3636.pdf
Oraby S, Harrison V, Reed L, Hernandez E, Riloff E, Walker MA (2016) Creating and characterizing a diverse corpus of sarcasm in dialogue. In: Proceedings of the SIGDIAL 2016 conference, The 17th annual meeting of the special interest group on discourse and dialogue, 13–15 September 2016, Los Angeles, CA, USA, pp 31–41. http://aclweb.org/anthology/W/W16/W16-3604.pdf
Oraby S, Reed L, Compton R, Riloff E, Walker MA, Whittaker S (2015) And that’s a fact: distinguishing factual and emotional argumentation in online dialogue. In: Proceedings of the 2nd workshop on argumentation mining, ArgMining@HLT-NAACL 2015, June 4, 2015, Denver, Colorado, USA, pp 116–126. http://aclweb.org/anthology/W/W15/W15-0515.pdf
Price P, Hirschman L, Shriberg E, Wade E (1992) Subject-based evaluation measures for interactive spoken language systems. In: Proceedings of the workshop on speech and natural language, pp 34–39. Association for Computational Linguistics
Ritter A, Cherry C, Dolan WB (2011) Data-driven response generation in social media. In: Proceedings of the conference on empirical methods in natural language processing. Association for Computational Linguistics
Serban IV, Lowe R, Charlin L, Pineau J (2015) A survey of available corpora for building data-driven dialogue systems. CoRR abs/1512.05742
Sordoni A, Galley M, Auli M, Brockett C, Ji Y, Mitchell M, Nie JY, Gao J, Dolan B (2015) A neural network approach to context-sensitive generation of conversational responses. arXiv preprint http://arxiv.org/abs/1506.06714
Swanson R, Gordon AS (2008) Say anything: a massively collaborative open domain story writing companion. In: Interactive storytelling. Springer, pp 32–40
Tsiakoulis P, Gasic M, Henderson M, Plannels J, Prombonas J, Thomson B, Yu K, Young S, Tzirkel E (2012) Statistical methods for building robust spoken dialogue systems in an automobile. In: in 4th international conference on applied human factors and ergonomics
Vinyals O, Le Q (2015) A neural conversational model. arXiv preprint http://arxiv.org/abs/1506.05869 (2015)
Walker MA, Litman DJ, Kamm CA, Abella A (1997) Paradise: a framework for evaluating spoken dialogue agents. In: Proceedings of the eighth conference on european chapter of the association for computational linguistics, pp 271–280. Association for Computational Linguistics
Walker MA, Passonneau R, Boland JE (2001) Quantitative and qualitative evaluation of darpa communicator spoken dialogue systems. In: Proceedings of the 39th annual meeting on association for computational linguistics, pp 515–522. Association for Computational Linguistics
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Bowden, K.K., Oraby, S., Misra, A., Wu, J., Lukin, S., Walker, M. (2019). Data-Driven Dialogue Systems for Social Agents. In: Eskenazi, M., Devillers, L., Mariani, J. (eds) Advanced Social Interaction with Agents . Lecture Notes in Electrical Engineering, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-319-92108-2_6
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