# Can Gestural Filler Reduce User-Perceived Latency in Conversation with Digital Humans?
## 1 Introduction  
The term digital human is generally used to refer to a computer-generated human-like entity. It is often interchangeably used with virtual human (VH) or, with the popularity of the terms metaverse and artificial intelligence (AI), is also called meta-human or AI beings [1]. While the latter two terms arose recently, VH has been used for decades in the virtual reality (VR) community and still is an active research topic [2; 3; 4; 5]. In VR, like those other virtual objects, the VH is comprised of computer graphics; however, VHs incorporated with physical body parts (e.g., with mannequins or robots) have also been proposed in the past couple of decades [6; 7; 8]. Nevertheless, 3D computer graphics had remained an essential characteristic of VHs when it came to their appearance. On the other hand, in the AI community, instead of 3D modeling and rendering, research on synthesizing human-like entities directly on 2D image or video has been produced [9]. Deep-neural-network-based models not only generate photo-realistic human images, but also synthesize voice, lip sync motion, and gestures [10; 11; 12]. Thus, the notion of the VH, which implicates 3D computer graphics, became insufficient to cover those AI-based synthesized humans. To cover both AI-based and 3D-modeled synthesized humans, we use the term digital human throughout this article. When facing digital humans, users might expect the same social interaction as they would with real humans (RHs), which has been widely investigated with the concept of social presence [13; 14]. Making social interaction directly relates to the intelligence of digital humans. Of course, achieving the human level of social interaction is still far from reality. However, in VR, digital humans, i.e., VHs, can be inhabited by users and interact socially with other VHs [15]. Those types of VHs are called avatars, contrary to the agents that are controlled by a computer program. When agents can make conversation with RHs,they are categorized as conversational agents [16]; furthermore, with the manifestation in the form of a human shape, they are called embodied conversational agents (ECAs) [17]. The digital transformation we are undergoing in the era of Industry 4.0 has enabled the accumulation of big data, and with big data, deep-neural-network-based AI models are widely adopted and improved, making agents rapidly intelligent. In the meantime, such digital transformation also have affected and improved the systems and processes of our society and industry, now demanding the paradigm shift from efficiency- and productivity-centric to human-centric in the upcoming Industry 5.0 and Society 5.0. In Society 5.0, digital humans are expected to co-exist with RHs and be socially more engaging in the form of cobots and/or human digital twins [18; 19]. With the recent development of AI models and natural language processing (NLP), the demand for a conversational system with a digital human has increased. There have been attempts to utilize digital humans in various fields, such as health care, psychological consultation, and education [20; 21; 22]. Furthermore, researchers have studied ECAs to mimic conversation with an RH [23; 24]. These systems often consist of voice processing models, e.g., text-to-speech (TTS) and speech-to-text (STT), and dialogue-generation models. For example, users' utterances are converted into text through an STT model and then analyzed with NLP. Agents then generate responses in text with simple keywords and a sentence-matching-based answer generation [25; 26] or a pre-trained language model [27; 28], which then is converted into synthesized voice through a TTS model. Some conversational systems with digital humans also include models for generating natural behavior, such as lip sync and gestures [17; 24; 29; 30; 31]. Usually, conversational systems utilize the server-client model. On the client side, a digital human appears on a screen or in a virtual environment, verbalizing the generated sentences and exhibiting gestures.