Weakly and Strongly Constrained Dialogues for Language Learning

Claire Gardent 1 Alejandra Lorenzo 1 Laura Perez-Beltrachini 1 Lina Rojas-Barahona 1
1 SYNALP - Natural Language Processing : representations, inference and semantics
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : We present two dialogue systems for lan- guage learning which both restrict the di- alog to a specific domain thereby pro- moting robustness and the learning of a given vocabulary. The systems vary in how much they constrain the learner's answer : one system places no other constrain on the learner than that provided by the re- stricted domain and the dialog context ; the other provides the learner with an exercise whose solution is the expected answer. The first system uses supervised learning for simulating a human tutor whilst the second one uses natural language gener- ation techniques to produce grammar ex- ercises which guide the learner toward the expected answer.
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Communication dans un congrès
the 14th annual SIGdial Meeting on Discourse and Dialogue SIGDIAL 2013, Aug 2013, Metz, France. pp.357-359, 2013
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Claire Gardent, Alejandra Lorenzo, Laura Perez-Beltrachini, Lina Rojas-Barahona. Weakly and Strongly Constrained Dialogues for Language Learning. the 14th annual SIGdial Meeting on Discourse and Dialogue SIGDIAL 2013, Aug 2013, Metz, France. pp.357-359, 2013. 〈hal-00920608〉

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