Hanseob Kim
ABSTRACT
In this poster, we present Flow Human, a no-code system that generates conversational behavior of digital humans from the text. Our users only need to build a conversation flow they want to talk to customers using the flow-based authoring tool we developed. Our system then automatically generates the verbal and non-verbal behavior of digital humans along the conversation flow, interacts with customers, and collects feedback. We believe that this work can serve the potential to be distributed to various services that have not been introduced because of the challenging task of controlling multiple factors in digital humans (e.g., conversation flow, co-speech gestures, and facial animation).
- Ghazanfar Ali, Myungho Lee, and Jae-In Hwang. 2020. Automatic text-to-gesture rule generation for embodied conversational agents. Computer Animation and Virtual Worlds 31, 4-5 (2020), e1944. https://doi.org/10.1002/cav.1944Google Scholar
Cross Ref
- Arno Hartholt, David Traum, Stacy C Marsella, Ari Shapiro, Giota Stratou, Anton Leuski, Louis-Philippe Morency, and Jonathan Gratch. 2013. All together now. In International Workshop on Intelligent Virtual Agents. Springer, 368–381.Google ScholarCross Ref
- Hanseob Kim, Myungho Lee, Gerard J. Kim, and Jae-In Hwang. 2021. The Impacts of Visual Effects on User Perception With a Virtual Human in Augmented Reality Conflict Situations. IEEE Access 9(2021), 35300–35312. https://doi.org/10.1109/ACCESS.2021.3062037Google ScholarCross Ref
- Nils Reimers and Iryna Gurevych. 2019. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. https://arxiv.org/abs/1908.10084Google ScholarCross Ref
Index Terms
- No-code Digital Human for Conversational Behavior
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