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Latent Variable Dialogue Models and their Diversity

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Peer-reviewed

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Article

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Authors

Clark, SC 

Abstract

We present a dialogue generation model that directly captures the variability in possible responses to a given input, which reduces the ‘boring output’ issue of deterministic dialogue models. Experiments show that our model generates more diverse outputs than baseline models, and also generates more consistently acceptable output than sampling from a deterministic encoder-decoder model.

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15th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2017)

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EPSRC (1510349)