Continual Learning Dialogue Systems - Learning during Conversation
Sahisnu Mazumder, Bing Liu · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · 2022
Dialogue systems, commonly known as Chatbots, have gained escalating popularity in recent years due to their wide-spread applications in carrying out chit-chat conversations with users and accomplishing various tasks as personal assistants. However, they still have some major weaknesses. One key weakness is that they are typically trained from pre-collected and manually-labeled data and/or written with handcrafted rules. Their knowledge bases (KBs) are also fixed and pre-compiled by human experts. Due to the huge amount of manual effort involved, they are difficult to scale and also tend to produce many errors ought to their limited ability to understand natural language and the limited knowledge in their KBs. Thus, when these systems are deployed, the level of user satisfactory is often low.