P. Auer, N. Cesa-bianchi, Y. Freund, and R. E. Schapire, The nonstochastic multiarmed bandit problem, SIAM Journal on Computing, vol.32, issue.1, pp.48-77, 2002.

D. Bahdanau, K. Cho, and Y. Bengio, Neural machine translation by jointly learning to align and translate, 2014.

C. Callison-burch, M. Osborne, and P. Koehn, Re-evaluating the role of BLEU in machine translation research, EACL, pp.249-256, 2006.

A. C. Curry, H. Hastie, and V. Rieser, A review of evaluation techniques for social dialogue systems, Proceedings of the 1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents, pp.25-26, 2017.

O. Du?ek and F. Jur?í?ek, Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings, Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, vol.2, pp.45-51, 2016.

M. Fang, Y. Li, and T. Cohn, Learning how to active learn: A deep reinforcement learning approach, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp.595-605, 2017.

E. Ferreira, B. Jabaian, and F. Lefèvre, Zero-shot semantic parser for spoken language understanding, Proceedings of INTERSPEECH, 2015.
URL : https://hal.archives-ouvertes.fr/hal-02039937

E. Ferreira, A. Reiffers-masson, B. Jabaian, and F. Lefèvre, Adversarial bandit for online interactive active learning of zero-shot spoken language understanding, Proceedings of ICASSP, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02041621

A. Gatt and E. Krahmer, Survey of the state of the art in natural language generation: Core tasks, applications and evaluation, Journal of Artificial Intelligence Research, vol.61, pp.65-170, 2018.

P. Gotab, F. Béchet, and G. Damnati, Active learning for rule-based and corpusbased spoken language understanding models, IEEE Workshop on Automatic Speech Recognition & Understanding, pp.444-449, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01317421

F. Bassam-jabaian, L. Lefèvre, and . Besacier, A unified framework for translation and understanding allowing discriminative joint decoding for multilingual speech semantic interpretation, Computer Speech & Language, vol.35, pp.185-199, 2016.

I. Konstas and M. Lapata, A global model for concept-to-text generation, Journal of Artificial Intelligence Research, vol.48, pp.305-346, 2013.

L. Li, W. Chu, J. Langford, and R. E. Schapire, A contextual-bandit approach to personalized news article recommendation, Proceedings of the 19th International Conference on World Wide Web, WWW '10, pp.661-670, 2010.

F. Mairesse and M. A. Walker, Towards personality-based user adaptation: Psychologically informed stylistic language generation, User Modeling and User-Adapted Interaction, vol.20, issue.3, pp.227-278, 2010.

F. Mairesse, M. Ga?i´cga?i´c, F. Jur?í?ek, S. Keizer, B. Thomson et al., Phrase-based statistical language generation using graphical models and active learning, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL '10, pp.1552-1561, 2010.

F. Mairesse and S. Young, Stochastic language generation in dialogue using factored language models, Computational Linguistics, vol.40, issue.4, pp.763-799, 2014.

E. Manishina, B. Jabaian, S. Huet, and F. Lefèvre, Automatic corpus extension for data-driven natural language generation, Proceedings of LREC, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02021894

H. Mei, M. Bansal, and M. R. Walter, What to talk about and how? Selective generation using LSTMs with coarse-to-fine alignment, Proceedings of NAACL-HLT, 2016.

J. Novikova, O. Lemon, and V. Rieser, Crowd-sourcing NLG data: Pictures elicit better data, Proceedings of the 9th International Natural Language Generation conference, pp.265-273, 2016.

A. H. Oh and A. I. Rudnicky, Stochastic natural language generation for spoken dialog systems, Computer Speech & Language, vol.16, issue.3-4, pp.387-407, 2002.

K. Papineni, S. Roukos, T. Ward, and W. Zhu, BLEU: a method for automatic evaluation of machine translation, Proceedings of the 40th annual meeting on association for computational linguistics, 2002.

L. Perez, -. Beltrachini, and C. Gardent, Analysing data-to-text generation benchmarks, Proceedings of the 10th International Natural Language Generation conference, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01623832

O. Rambow, S. Bangalore, and M. Walker, Natural language generation in dialog systems, Proceedings of HLT, 2001.

E. Reiter and A. Belz, An investigation into the validity of some metrics for automatically evaluating natural language generation systems, Computational Linguistics, vol.35, issue.4, pp.529-558, 2009.

V. Rieser and O. Lemon, Reinforcement Learning for Adaptive Dialogue Systems: A Datadriven Methodology for Dialogue Management and Natural Language Generation. Theory and Applications of Natural Language Processing, 2011.

V. Iulian, A. Serban, Y. Sordoni, A. Bengio, J. Courville et al., Building end-to-end dialogue systems using generative hierarchical neural network models, Proceedings of AAAI Conference on Artificial Intelligence, 2016.

M. Walker, A. Stent, F. Mairesse, and R. Prasad, Individual and domain adaptation in sentence planning for dialogue, Journal of Artificial Intelligence Research, vol.30, issue.1, pp.413-456, 2007.

M. Tsung-hsien-wen, D. Ga?i´cga?i´c, N. Kim, P. Mrk?i´cmrk?i´c, D. Su et al., Stochastic language generation in dialogue using recurrent neural networks with convolutional sentence reranking, Proceedings of SIGDIAL, 2015.

M. Tsung-hsien-wen, N. Ga?i´cga?i´c, L. M. Mrk?i´cmrk?i´c, P. Rojas-barahona, D. Su et al., Toward multi-domain language generation using recurrent neural networks, Proceedings of NIPS Workshop on Machine Learning for Spoken Language Understanding and Interaction, 2015.

M. Tsung-hsien-wen, N. Ga?i´cga?i´c, P. Mrk?i´cmrk?i´c, D. Su, S. Vandyke et al., Semantically conditioned LSTM-based natural language generation for spoken dialogue systems, Proceedings of EMNLP, 2015.

M. Tsung-hsien-wen, N. Ga?i´cga?i´c, L. M. Mrk?i´cmrk?i´c, P. Rojas-barahona, S. Su et al., A network-based end-to-end trainable task-oriented dialogue system, 2016.

M. Tsung-hsien-wen, N. Ga?i´cga?i´c, L. M. Mrk?i´cmrk?i´c, P. Rojas-barahona, D. Su et al., Multi-domain neural network language generation for spoken dialogue systems, Proceedings of NAACL-HLT, 2016.