Papers by Matthew Roddy

1 papers
Neural Generation of Dialogue Response Timings (2020.acl-main)

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Challenge: Using neural models, the timings of spoken response offsets in human dialogue can vary based on contextual elements of the dialogue.
Approach: They propose neural models that simulate the distributions of response offsets taking into account the response turn as well as the preceding turn.
Outcome: The proposed models can generate distributions of response offsets based on the response turn and preceding turn based upon human listening tests and offline experiments.

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