论文标题
对话响应时间的神经产生时间
Neural Generation of Dialogue Response Timings
论文作者
论文摘要
根据对话的上下文元素，已经证明，人类对话中口语反应的时机偏移有所不同。我们提出了神经模型，以模拟这些响应偏移的分布，并考虑到响应转弯以及前面的转弯。这些模型旨在集成到增量口语对话系统（SDS）的管道中。我们使用离线实验以及人类听力测试评估了模型。我们表明，根据对话环境，人类听众认为某些响应时间更为自然。将这些模型引入SDS管道可能会增加相互作用的自然性。
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.
