# Can Gestural Filler Reduce User-Perceived Latency in Conversation with Digital Humans?
## 6 Conclusions  
In this paper, we demonstrated the potential of gestural fillers when latency occurs in the conversation with embodied conversational agents, i.e., digital humans. In Study 1, we examined whether the congruency between the gestural fillers and conversation types affects the user's perception of the embodied conversational agent. In two congruency conditions (informative conversation with typing motion and casual conversation with thinking motion), the participants evaluated the digital humans as more natural, as well as felt less latency, addressing RQ2. Furthermore, in Study 2, we further compared the effects of conversational and gestural fillers on the user's perception and gaze behavior, which gave answers to our RQ1 and RQ3. Our results indicated that gestural fillers could mitigate user-perceived latency more effectively than conversational fillers and make digital humans' behavior more natural. In addition, the gestural fillers positively affected users' willingness to talk to and impression of the digital humans, as well as their perceived competence, while reducing the discomfort the users felt. It goes without saying that gestural fillers were more effective in drawing users' attention than conversational fillers.  
While several interesting findings were drawn, there also are a few limitations to be noted. First, the digital human repeatedly exhibited the same gestural and conversational fillers per condition. For example, we used thinking motion with \"Wait a minute\" in the casual conversation type and typing motion with \"I am searching for information\" in the informative conversation type. Some participants pointed out that, _\"The digital human acted with the same pattern in three out of eight turn-takings.\"_ and she/he also stated _\"It was a little boring.\"_ and _\"If the digital human made various motions or used different words, the conversation would be less boring.\"_. To address this issue, we plan to build a gesture-generation model to generate appropriate gestural fillers based on the given conversation and context. Furthermore, the participants pointed out that the digital humans' intonation, gestures, and facial expressions were unnatural compared to real people.  
Those unnatural intonations, gestures, and facial cues might have been more substantial than latency; thus, further comparison studies should be conducted for better usability of conversational digital humans. Regarding latency, we utilized pre-determined scripts and pre-recorded audio files to exclude unintended latency factors, e.g., networking, inference time, etc. Those omitted factors should be mathematically modeled to determine when to initiate fillers in practice. Finally, all participants were Koreans; thus, the cultural diversity of the participants was limited. The gestures and utterances used in this study can be perceived differently outside Korea, similar to the meaning of nodding one's head in India differs from most other countries. Therefore, future work should consider including participants from various cultural backgrounds.  
Conceptualization, J.K. and M.L.; Data curation, J.K.; Formal analysis, J.K. and M.L.; Funding acquisition, M.L.; Investigation, J.K.; Methodology, J.K. and M.L.; Software, J.K.; Visualization, J.K.; Writing--original draft, J.K.; Writing--review & editing, M.L. All authors have read and agreed to the published version of the manuscript.  
This research is supported by Year 2021 Culture Technology R&D Program by Ministry of Culture, Sports and Tourism and Korea Creative Content Agency (Project Number: R2021040269).  
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Pusan National University (protocol code 2022-76-HR, 3 August 2022).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Data Availability Statement: Not applicable.  
The authors declare no conflict of interest.