Recent advances in deep learning based dialogue systems: a systematic survey

Dialogue systems are a popular natural language processing (NLP) task as it is promising in real-life applications. It also complicated since many NLP tasks deserving study involved. As result, multitude of novel works on this carried out, and most them deep learning based due to their outstanding performance. In survey, we mainly focus the dialogue systems. We comprehensively review state-of-the-art research outcomes analyze from two angles: model type system type. Specifically, angle type, discuss principles, characteristics, applications different models that widely used This will help researchers acquaint these see how they applied frameworks, which rather helpful when designing new system. From task-oriented open-domain streams research, providing insight into hot topics related. Furthermore, evaluation methods datasets for pave way future research. Finally, some possible trends identified recent outcomes. To best our knowledge, survey comprehensive up-to-date one at present systems, extensively covering techniques. speculate work good starting point academics who or those want quickly grasp techniques area.