Audio-driven Robot Upper-body Motion Synthesis

Body language is an important aspect of human communication, which an effective human-robot interaction interface should mimic well. The currently available robotic platforms are limited in their ability to automatically generate behaviours that align with their speech. In this paper, we developed a neural network based system that takes audio from a user as an input and generates upper-body gestures including head, hand and hip movements of the user on a humanoid robot, namely, Softbank Robotics’ Pepper. The developed system was evaluated quantitatively as well as qualitatively using web-surveys when driven by natural speech and synthetic speech. We particularly compared the impact of generic and person-specific neural network models on the quality of synthesised movements. We further investigated the relationships between quantitative and qualitative evaluations and examined how the speaker’s personality traits affect the synthesised movements

Trust in interdependent and task-oriented human-computer cooperation

Kulms P. Trust in interdependent and task-oriented human-computer cooperation. Bielefeld: Universität Bielefeld; 2018.This thesis presents a new paradigm for the modeling of cooperative human–computer interaction in order to evaluate the antecedents, formation, and regulation of human–computer trust. Human–computer trust is the degree to which human users trust computers to help them achieve their goals, and functions as powerful psychological variable that governs user behavior. The modeling framework presented in this thesis aims to extend predominant methods for the study of trust and cooperation by building on competent problemsolving and equal goal contributions by users and computers. Specifically, the framework permits users to participate in interactive and interdependent decision-making games with autonomous computer agents. The main task is to solve a two-dimensional puzzle, similar to the popular game Tetris. The games derived from this framework include cooperative interaction factors known from interpersonal cooperation: the duality of competence and selfishness, anthropomorphism, task advice, and social blame. One validation study (68 participants) and four experiments (318 participants) investigate how these cooperative interaction factors influence human–computer trust. In particular, the results show how trust in computers is mediated by warmth as universal dimension of social cognition, how anthropomorphism of computers influences trust formation over time, and how expressive anthropomorphic cues can be used to regulate trust. We explain how these findings can be applied to design trustworthy computer agents for successful cooperation

Real-Time Visual Prosody for Interactive Virtual Agents

van Welbergen H, Ding Y, Sattler K, Pelachaud C, Kopp S. Real-Time Visual Prosody for Interactive Virtual Agents. In: Brinkman W-P, Broekens J, Heylen D, eds. Intelligent Virtual Agents. Lecture Notes in Computer Science. Vol 9238. Cham: Springer International Publishing; 2015: 139-151.Speakers accompany their speech with incessant, subtle head movements. It is important to implement such “visual prosody” in virtual agents, not only to make their behavior more natural, but also because it has been shown to help listeners understand speech. We contribute a visual prosody model for interactive virtual agents that shall be capable of having live, non-scripted interactions with humans and thus have to use Text-To-Speech rather than recorded speech. We present our method for creating visual prosody online from continuous TTS output, and we report results from three crowdsourcing experiments carried out to see if and to what extent it can help in enhancing the interaction experience with an agent

Real-time Visual Prosody for Interactive Virtual Agents

International audience<p>Speakers accompany their speech with incessant, subtle headmovements. It is important to implement such &quot;visual prosody&quot; in virtual agents, not only to make their behavior more natural, but also because it has been shown to help listeners understand speech. We contribute a visual prosody model for interactive virtual agents that shall be capableof having live, non-scripted interactions with humans and thus have to use Text-To-Speech rather than recorded speech. We present our method for creating visual prosody online from continuous TTS output, and we report results from three crowdsourcing experiments carried out to seeif and to what extent it can help in enhancing the interaction experience with an agent.</p