1. Paper title
Neural Generation of Dialogue Response Timings
2. link
https://www.aclweb.org/anthology/2020.acl-main.221.pdf
3. 摘要
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.1
4. 要解决什么问题
人对对话的响应时间是随机的。
5. 作者的主要贡献
根据对话内容计算合适的响应时间，并把这种响应时间加入到SDS中。
6. 得到了什么结果
听到带响应时间的应答让人觉得更自然。
7. 关键字
响应时间， 自然