OLD cours 1 EIDI - introduction aux systèmes de dialogue | EIDI 2019

Support de cours

Hahn et al., Comparing stochastic approaches to spoken language understanding in multiple languages. TALSP 2010. PDF
Yao et al., Spoken language understanding using long short-term memory neural networks. SLT 2014. PDF
Mesnil et al., Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding. TASLP 2015. PDF
Guo et al., Joint semantic utterance classification and slot filling with recursive neural networks. SLT 2014. PDF
Zhang et al., A Joint Model of Intent Determination and Slot Filling for Spoken Language Understanding. IJCAI 2016. PDF
Villaneau et Antoine, Categorials grammars used to partial parsing of spoken language. CG 2004. PDF
Galibert, pproaches and methodologies for automatic Question-Answering in an open-domain, interactive setup. PhD thesis, Paris Sud. 2009. PDF
Campillos Llanos et al., Managing Linguistic and Terminological Variation in a Medical Dialogue System. LREC 2016. PDF
Glass et al., Multilingual spoken-language understanding in the MIT Voyager system. Speech Communication 17, 1995. PDF

Traum et Larsson, The information state approach to dialogue management. In “Current and new directions in discourse and dialogue”, Springer 2003.
Hori et al., Context sensitive spoken language understanding using role dependent lstm layers. Machine Learning for SLU Interaction NIPS 2015 Workshop 2015. PDF
Chen et al., End-to-End Memory Networks with Knowledge Carryover for Multi-Turn Spoken Language Understanding. Interspeech 2016. PDF

Henderson, Machine learning for dialog state tracking: A review. Machine Learning in Spoken Language Processing Workshop, 2015. PDF
Larsson et Traum, Information state and dialogue management in the TRINDI dialogue move engine toolkit. Natural language engineering 6, 2000. PDF
Young et al., The hidden information state approach to dialog management. ICASSP, 2007. PDF
Thomson et Young, Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems. CSL 24:4, 2010. PDF
Metallinou et al., Discriminative state tracking for spoken dialog systems. SIGDIAL, 2013. PDF
Henderson et al., Deep neural network approach for the dialog state tracking challenge. SIGDIAL, 2013. PDF
Young, Using POMDPs for dialog management. SLT, 2006. PDF
Sutton et Barto, Reinforcement learning: An introduction. MIT Press. PDF
Schatzmann et al., A survey of statistical user simulation techniques for reinforcement-learning of dialogue management strategies. The knowledge engineering review 21:2, 2006. PDF
Wen et al., A Network-based End-to-End Trainable Task-oriented Dialogue System. EACL 2017. PDF
Williams et al., Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. ACL 2017. PDF

Rambow et al., Natural language generation in dialog systems. HLT 2001. PDF
Mairesse et al., Phrase-based statistical language generation using graphical models and active learning. ACL 2010. PDF
Dethlefs et al., Conditional Random Fields for Responsive Surface Realisation using Global Features. ACL, 2013. PDF

Banchs et Li, {IRIS}: a chat-oriented dialogue system based on the vector space model. ACL 2012. PDF
Gandhe et Traum, Surface text based dialogue models for virtual humans. SigDial 2013. PDF
Lowe et al., The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems. SigDial 2015. PDF
Ameixa et al., {I} am your father: dealing with out-of-domain requests by using movies subtitles. IVA 2014. PDF
Nio et al., Developing non-goal dialog system based on examples of drama television. In: Natural {Interaction} with {Robots}, {Knowbots} and {Smartphones}, pp. 355–361. Springer. PDF

Bonneau-Maynard et al., Results of the French Evalda-Media evaluation campaign for literal understanding. LREC 2006. PDF
Dialog State Tracking Challenges Website
Schmitt et al., A parameterized and annotated spoken dialog corpus of the cmu let’s go bus information system. LREC, 2012. PDF

Dybkjaer et al., Evaluation and usability of multimodal spoken language dialogue systems. Speech Communication, 2004. PDF
Walker et al., Paradise: a framework for evaluating spoken dialogue agents. EACL, 1997. PDF
Hone et Graham, Towards a tool for the subjective assessment of speech system interfaces (sassi). Natural Language Engineering 6, 2000. PDF
Schmitt et al., WITcHCRafT: A Workbench for Intelligent exploraTion of Human ComputeR conversaTions. LREC, 2010. PDF
Witt, A global experience metric for dialog management in spoken dialog systems. SemDial 2011. PDF
Higashinaka et al., Towards taxonomy of errors in chat-oriented dialogue systems. SigDial 2015. PDF

Liu et al., How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. EMNLP 2016. PDF
Dubuisson Duplessis et al., Purely Corpus-based Automatic Conversation Authoring. LREC, 2016. PDF
Charras et al., Comparing System-response Retrieval Models for Open-domain and Casual Conversational Agent. In WOCHAT workshop, IVA, 2016. PDF
Lowe et al., Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses. ACL 2017. PDF
Dubuisson Duplessis et al., Utterance Retrieval based on Recurrent Surface Text Patterns. ECIR 2017. PDF

Athavale et al., Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity. ICON 2016. PDF
Lavergne et al., Practical very large scale CRFs. ACL 2010 PDF