In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses. However, for real application in online systems, high QPS (queries per second, an indicator of the flow capacity of on-line systems) is required, and a dynamic vocabulary mechanism has been proved available in improving speed of generative models. In this paper, we proposed an emotion-controlled dialog response generation model based on the dynamic vocabulary mechanism, and the experimental results show the benefit of this model.
@article{arxiv.2103.02878,
title = {An Emotion-controlled Dialog Response Generation Model with Dynamic Vocabulary},
author = {Shuangyong Song and Kexin Wang and Chao Wang and Haiqing Chen and Huan Chen},
journal= {arXiv preprint arXiv:2103.02878},
year = {2021}
}