000 Informatik, Informationswissenschaft, allgemeine Werke
Refine
Year of publication
Document Type
- Conference Proceeding (108)
- Article (32)
- Part of a Book (27)
- Workingpaper / Report (21)
- Other (11)
- Master's Thesis (7)
- Bachelor Thesis (5)
- Collection (2)
- Preprint (2)
- Study Thesis (2)
Language
- English (121)
- German (97)
- Multiple languages (4)
Keywords
- FHD (26)
- Virtual (TV) Studio (13)
- Agilität (12)
- VSVR (12)
- Digitale Lehre (9)
- security (9)
- Aussendarstellung (8)
- security requirement (7)
- Datenbanken (6)
- E-Business (6)
Department/institution
- Fachbereich - Medien (196)
- Digital Learning and Digital Literacy (33)
- Digitale Vernetzung und Informationssicherheit (33)
- Creative Media Production and Entertainment Computing (28)
- Campus IT (10)
- Sound and Vibration Engineering (9)
- Intelligente Mensch-Technik-Interaktion (7)
- Fachbereich - Maschinenbau und Verfahrenstechnik (3)
- Fachbereich - Architektur (2)
- Fachbereich - Design (2)
Prior research has reported differential roles of valence and arousal in guiding memory and attention. However, few studies have systematically examined how these affective dimensions interact across their full spectrum in audiovisual contexts, particularly when multiple images varying in emotional content are simultaneously present. To address this, we used a recognition memory paradigm in which participants viewed arrays of images representing all combinations of positive/negative valence and low/high arousal. Slightly before and during image presentation, music conveying an emotional tone, also varying in valence and arousal, was played. Memory accuracy was assessed in a later recognition phase. We further employed simple eye-tracking measures to explore how visual attention is influenced by image and music valence and arousal. Results revealed that high image arousal increases fixation duration, whilst high music arousal decreases fixation duration. Memorisation likelihood was not influenced by a four-way interaction of image and music valence and arousal, but mainly by an interaction of image valence and arousal, differently depending on music arousal. In high music arousal, all images except low arousal positive images, were memorised regardless of valence. In low arousal music, we observed that memorisation likelihood was mainly driven by high image arousal, but only paired with negative image valence was memorisation significantly higher compared to other image types. Discrimination accuracy was not observed to be influenced by image valence and arousal, but positive high arousal music significantly improved memory discrimination. By systematically manipulating both valence and arousal of images and music, we highlight how the interaction of these unimodal affective qualities can facilitate or hinder memory.
The growing burden of mental illness and limited access to evidence-based psychotherapy have increased interest in artificial intelligence (AI)–driven conversational agents as potential supports for mental health care. In this exploratory pilot study, we examined the safety and feasibility of an intelligent virtual agent (IVA) designed to simulate psychotherapeutic interactions, with a focus on high-risk situations involving suicidality and substance use. Two licensed psychotherapists engaged in scripted interactions with the IVA across 12 predefined scenarios addressing suicidality and substance abuse. The IVA was powered by GPT-4omni and embedded in a Unity-based avatar. After each interaction, testers evaluated acceptance, usability, and human–robot interaction. Two independent psychotherapists rated the IVA’s responses using a structured scale assessing guideline adherence, risk recognition, help provision, de-escalation, and empathy. No real patients were involved; all interactions were simulated for safety testing purposes. The IVA showed preliminary indications of good usability and generally empathic responses. However, problematic responses occurred in 29% of conversations, with 12.5% rated as highly critical. Responses rated as “critical” or “highly critical” referred to outputs that failed to provide adequate support, showed insufficient risk recognition, or included ethically problematic suggestions. Key concerns included inadequate recognition of risk, normalization of substance use, and insufficient referral to crisis resources, particularly in scenarios involving underage alcohol access and suicide-related inquiries. In this small, expert-based pilot safety evaluation, the findings suggest that although AI-based agents may improve access to mental health support, rigorous safety evaluation, clinical oversight, and robust safeguards are essential prior to clinical deployment. No clinical conclusions can be drawn from this simulated study.
High-Resolution Directivity Measurements of an Artificial Head and Mouth Shaped to Three Vowels
(2026)
The directivity of the human voice has been studied since the early twentieth century using different measurement systems with progressively higher spatial resolution. Artificial heads and mouths have been used because of their ability to repeat a given sound production, hence allowing sequential measurements of directivity with a reduced number of microphones and still achieving high spatial resolution. Unlike most artificial heads, whose external geometry is abstracted, this study uses a custom 3D-printed head with detailed geometry and three different mouth openings, all based on 3D scans from magnetic resonance imaging data. The impulse response measurements were performed using a 3D robotic arm, resulting in directivity data with 5° resolution in both azimuth and elevation. The measured directivity patterns are consistent with previous research on energy distribution in space over angles (azimuth and elevation) and frequency, with a higher spatial resolution and for different mouth shapes. The resulting data set is made available in several standardized file formats to facilitate accurate voice directivity simulations in virtual acoustic environments.