2018
ACL
ACL 2018
Personalizing Dialogue Agents: I have a dog, do you have pets too?
Abstract
AbstractChit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating. In this work we present the task of making chit-chat more engaging by conditioning on profile information. We collect data and train models to (i)condition on their given profile information; and (ii) information about the person they are talking to, resulting in improved dialogues, as measured by next utterance prediction. Since (ii) is initially unknown our model is trained to engage its partner with personal topics, and we show the resulting dialogue can be used to predict profile information about the interlocutors.
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The Questioner
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Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
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Keyword Pioneer
— utterance prediction
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Hot Topic Early Bird
— dialogue generation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio