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- W4287777436 abstract "The timings of spoken response offsets in human dialogue have been shown to vary based on contextual elements of the dialogue. We propose neural models that simulate the distributions of these response offsets, taking into account the response turn as well as the preceding turn. The models are designed to be integrated into the pipeline of an incremental spoken dialogue system (SDS). We evaluate our models using offline experiments as well as human listening tests. We show that human listeners consider certain response timings to be more natural based on the dialogue context. The introduction of these models into SDS pipelines could increase the perceived naturalness of interactions." @default.
- W4287777436 created "2022-07-26" @default.
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- W4287777436 date "2020-05-18" @default.
- W4287777436 modified "2023-10-17" @default.
- W4287777436 title "Neural Generation of Dialogue Response Timings" @default.
- W4287777436 doi "https://doi.org/10.48550/arxiv.2005.09128" @default.
- W4287777436 hasPublicationYear "2020" @default.
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