Dialogue Context Modelling for Action Item Detection: Solution for ICASSP 2023 Mug Challenge Track 5

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(2023)

引用 0|浏览18
暂无评分
摘要
Action item detection aims at recognizing sentences containing information about actionable tasks, which can help people quickly grasp core tasks in the meeting without going through the redundant meeting contents. Therefore, in this paper, we thoroughly describe our carefully designed solution for the Action Item Detection Track of the General Meeting Understanding and Generation (MUG) challenge in the ICASSP 2023 Signal Processing Grand Challenge. Specifically, we systematically analyze the task instances provided by MUG and find that the key ingredient for successful action item detection is leveraging the dialogue context information into consideration. To this end, we design a simple and effective method for modelling context and utterance information concurrently. The experimental results show our method achieves remarkable improvements over baseline models, with an absolute increase of 0.62 of the F 1 score on the validation set. The stable generalizability of our method is further verified by our score on the final test set 1 .
更多
查看译文
关键词
Natural Language Processing,Meeting Understanding,Action Item Detection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要