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      Addressee and Response Selection for Multilingual Conversation

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          Abstract

          Developing conversational systems that can converse in many languages is an interesting challenge for natural language processing. In this paper, we introduce multilingual addressee and response selection. In this task, a conversational system predicts an appropriate addressee and response for an input message in multiple languages. A key to developing such multilingual responding systems is how to utilize high-resource language data to compensate for low-resource language data. We present several knowledge transfer methods for conversational systems. To evaluate our methods, we create a new multilingual conversation dataset. Experiments on the dataset demonstrate the effectiveness of our methods.

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          How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

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            The fifth dialog state tracking challenge

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              Issues in Multiparty Dialogues

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                Author and article information

                Journal
                12 August 2018
                Article
                1808.03915
                c56a2620-4617-4462-aaff-838a67647c3d

                http://creativecommons.org/licenses/by/4.0/

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                Custom metadata
                coling 2018
                cs.CL

                Theoretical computer science
                Theoretical computer science

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