Speaker-oriented Conversation Model and its Evaluation
JinYeong Bak is an assistant professor in the colleague of computing at Sungkyunkwan
University. His research interests analyzing human behaviors from their conversations and building open-domain conversation models from the insights of the analysis. He worked at Microsoft Research Asia as a research intern and United Nations Global Pulse Lab Jakarta as a junior data scientist. He received Ph.D. and M.S. from the KAIST and a B.S. from Sungkyunkwan University. His research has been published in ACL, EMNLP, CHI, and ICWSM. His personal homepage: https://nosyu.github.io
Many neural network-based open-domain conversation models have seen successes in recent years. Despite these recent successes, the open-domain conversation models still have challenges to imitate human-level conversations. One of the challenges is the consideration of speakers in the conversations. Knowing information about a speaker, such as her linguistic style or personal information can help predict her response, and knowing more about both speakers from their previous conversations can help predict the contents of their conversation. My research focuses on modeling speakers and their behaviors in the conversations that enable conversation model to generate human-like responses. In this talk, I will introduce two recent research projects on conversation modeling: generating personalized conversational responses (EMNLP 2019) and evaluating conversational responses without human-labeled data (ACL 2020). I will also show future directions of my research to build conversation models that consider various conversation characteristics such as topics, intensions, and multimodality.
ZOOM : https://zoom.us/j/8978217407?pwd=d1pOZmF1OWlseEdZRVBpV3VuSkl3dz09
ID : 897 821 7407
PW : 1nTQDY