4 accepted papers
Co-speech gestures are a key channel of human communication, making them important for personalized chat agents to generate. In the past, gesture generation models assumed that data for each speaker is available all at once, and in large amounts. However in practical scenarios, speaker data comes se…
This study investigated differences in the contributions of various features to in-person (IP) and video-mediated (VM) meetings. We focused on estimating important utterances using both an IP and a VM meeting corpora as the analysis data. A transformer model with dialogue history was used to estimat…
Mental health conditions remain underdiagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily collectible data has several important implications for the early detection, intervention, and treatment of mental health d…
We proposed a model for predicting the next speaker in multi-party meetings by focusing on the participants' head movements measured by using a six degrees-of-freedom head tracker. Results of an analysis of head movements collected from multi-party meetings revealed differences in the amounts, ampli…