[PDF] Learning to Personalize Spoken Generation for Dialogue Systems
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Abstract. One of the most robust findings of studies of human-human di- alogue is that people adapt their utterances to their conversa- tional partners.
In this paper, we utilize one statistical method, boosting, to train a spoken language generator for individual users. We show that individualized models ...
Nov 12, 2019 · This paper proposes a pre-training based personalized dialogue model that can generate coherent responses using persona-sparse dialogue data.
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What is a dialogue generation system?
Recent studies try to tackle the personalized dialogue generation problem in a data-driven manner, i.e., learning persona related features directly from large- ...
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Personalized dialogue systems explore the problem of generating responses that are consistent with the user's personality, which has raised much attention ...
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Mar 14, 2023 · We introduce dGSLM, the first “textless” model able to generate audio samples of naturalistic spoken dialogues.
ABSTRACT. Spoken dialogue systems must be able to recover gracefully from unexpected user inputs. In many cases, these unexpected utterances.
Dec 10, 2023 · Personalized dialogue generation, focusing on generating highly tailored responses by lever- aging persona profiles and dialogue context,.
Apr 18, 2022 · Existing personalized dialogue systems have tried to extract user profiles from dialogue history to guide personalized response generation.
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This class of statistical generators can learn generation decisions directly from dialogue act (DA)-utterance pairs without any semantic annotations (Mairesse ...