http://dl.gi.de/handle/20.500.12116/11105 2026-07-23T18:35:23Z 2026-07-23T18:35:23Z Becker-Asano, Christian http://dl.gi.de/handle/20.500.12116/11218 2018-03-20T10:33:08Z 2011-01-01T00:00:00Z

Affective Computing Combined with Android Science Becker-Asano, Christian In this report a number of research projects are summarized that aimed at investigating the emotional effects of android robots. In particular, those robots are focused on that have been developed and are incessantly being improved by Hiroshi Ishiguro at both the Advanced Telecommunications Research Institute International (ATR) in Kyoto and Osaka University in Osaka, Japan. Parts of the reported empirical research have been conducted by the author himself during a two-year research stay at ATR as post-doctoral fellow of the Japan Society for the Promotion of Science.In conclusion, Affective Computing research is taken to the next level by employing physical androids rather than purely virtual humans, and Android Science benefits from the experience of the Affective Computing community in devising means to assess and evaluate a human observer’s subjective impressions that android robots give rise to.

2011-01-01T00:00:00Z Wöllmer, Martin Weninger, Felix Eyben, Florian Schuller, Björn http://dl.gi.de/handle/20.500.12116/11220 2018-03-20T10:33:08Z 2011-01-01T00:00:00Z

Computational Assessment of Interest in Speech—Facing the Real-Life Challenge Wöllmer, Martin; Weninger, Felix; Eyben, Florian; Schuller, Björn Automatic detection of a speaker’s level of interest is of high relevance for many applications, such as automatic customer care, tutoring systems, or affective agents. However, as the latest Interspeech 2010 Paralinguistic Challenge has shown, reliable estimation of non-prototypical natural interest in spontaneous conversations independent of the subject still remains a challenge. In this article, we introduce a fully automatic combination of brute-forced acoustic features, linguistic analysis, and non-linguistic vocalizations, exploiting cross-entity information in an early feature fusion. Linguistic information is based on speech recognition by a multi-stream approach fusing context-sensitive phoneme predictions and standard acoustic features. We provide subject-independent results for interest assessment using Bidirectional Long Short-Term Memory networks on the official Challenge task and show that our proposed system leads to the best recognition accuracies that have ever been reported for this task. The according TUM AVIC corpus consists of highly spontaneous speech from face-to-face commercial presentations. The techniques presented in this article are also used in the SEMAINE system, which features an emotion sensitive embodied conversational agent.

2011-01-01T00:00:00Z Reichardt, Dirk M. http://dl.gi.de/handle/20.500.12116/11223 2018-03-20T10:33:08Z 2011-01-01T00:00:00Z

Interview with Rosalind Picard Reichardt, Dirk M.

2011-01-01T00:00:00Z Boukricha, Hana Wachsmuth, Ipke http://dl.gi.de/handle/20.500.12116/11219 2018-03-20T10:33:08Z 2011-01-01T00:00:00Z

Empathy-Based Emotional Alignment for a Virtual Human: A Three-Step Approach Boukricha, Hana; Wachsmuth, Ipke Allowing virtual humans to align to others’ perceived emotions is believed to enhance their cooperative and communicative social skills. In our work, emotional alignment is realized by endowing a virtual human with the ability to empathize. Recent research shows that humans empathize with each other to different degrees depending on several factors including, among others, their mood, their personality, and their social relationships. Although providing virtual humans with features like affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such features as factors modulating their empathic behavior. Supported by psychological models of empathy, we propose an approach to model empathy for the virtual human EMMA—an Empathic MultiModal Agent—consisting of three processing steps: First, the Empathy Mechanism by which an empathic emotion is produced. Second, the Empathy Modulation by which the empathic emotion is modulated. Third, the Expression of Empathy by which EMMA’s multiple modalities are triggered through the modulated empathic emotion. The proposed model of empathy is illustrated in a conversational agent scenario involving the virtual humans MAX and EMMA.

2011-01-01T00:00:00Z