Björn W Schuller
Biographic Data
| ID | 3461765 |
|---|---|
| NAME | Björn W Schuller |
| GIVEN NAMES | Björn W |
| FAMILY NAME | Schuller |
| SIGNATURE | SCHULLER B W |
| AFFILIATIONS | University of Augsburg |
| ORCID | 0000-0002-6478-8699 |
| VERIFIED | Yes |
| TOTAL WORKS | 21 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 21 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Guidelines for Emotion Recognition in Robot-Supported Interventions in Autism
Therapy for children with autism spectrum disorder benefits from the use of diverse technologies, as most children with the condition are eager to interact with them. The integration of emotion recognition technologies with social robots offers promising opportunities to make therapeutic interactions more adaptive, personalized, and responsive to a child’s emotional state, potentially improving engagement and learning outcomes. The purpose of thi…
Creating Healthier Living Environments: The Role of Soundscapes in Promoting Mental Health and Well-Being
Quality in science communication with communicative artificial intelligence: A principle-based framework
The rapid advancement of communicative artificial intelligence (ComAI) is profoundly impacting science communication, offering new opportunities for easier and more audience-oriented communication. However, it also poses several challenges for its practice. Based on a narrative review of literature on science communication and ComAI quality, this article develops a framework of quality principles for science communication with ComAI. The framewor…
Bridging acute and chronic stress effects on inflammation: Protocol for a mixed-methods intensive longitudinal study
Acute stress triggers adaptive physiological responses-including transient increases in inflammatory cytokines-while chronic stress is associated with sustained inflammatory activity that may underlie the development of various disorders. Despite extensive research on each stress type individually, the transition and interaction between them remain underexplored. This study aims to address this gap by employing an intensive longitudinal measureme…
Refashioning Emotion Recognition Modeling: The Advent of Generalized Large Models
After its inception, emotion recognition or affective computing has increasingly become an active research topic due to its broad applications. The corresponding computational models have gradually migrated from statistically shallow models to neural-network-based deep models, which can significantly boost the performance of emotion recognition and consistently achieve the best results on different benchmarks, and thus has been considered the fir…
Challenges in Observing the Emotions of Children with Autism Interacting with a Social Robot
This paper concerns the methodology of multi-modal data acquisition in observing emotions experienced by children with autism while they interact with a social robot. As robot-enhanced therapy gains more and more attention and proved to be effective in autism, such observations might influence the future development and use of such technologies. The paper is based on an observational study of child-robot interaction, during which multiple modalit…
Establishing the reliability of metrics extracted from long-form recordings using Lena and the Aclew pipeline
Long-form audio recordings are increasingly used to study individual variation, group differences, and many other topics in theoretical and applied fields of developmental science, particularly for the description of children's language input (typically speech from adults) and children's language output (ranging from babble to sentences). The proprietary LENA software has been available for over a decade, and with it, users have come to rely on d…
Intelligent Music Intervention for Mental Disorders: Insights and Perspectives
Welcome to the first issue of IEEE Transactions on Computational Social Systems (TCSS) of 2023. The past 2022 was again a very productive year, in which we have published 159 articles with about 1850 pages in six issues. We also received much great and exciting news
Can a Holistic View Facilitate the Development of Intelligent Traditional Chinese Medicine? A Survey
Intelligent traditional Chinese medicine (ITCM) is an emerging interdisciplinary subject. It aims to efficiently and precisely promote the prevention and treatment of diseases and health management in Chinese medicine clinical practice via the combination of traditional Chinese medicine (TCM) fundamentals and artificial intelligence technologies. Presently, it is experiencing dramatic growth in recent years. On the one hand, a holistic view, as a…
The promise of digital healthcare technologies
Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthe…
Digital Mental Health—Breaking a Lance for Prevention
Welcome to the last issue of IEEE Transactions On Computational Social Systems (TCSS) of 2022. In this issue, we publish a Special Issue on Advanced Cognitive Computing for Data-Driven Computational Social Systems, which includes 23 articles. Moreover, we also would like to share some of our opinions and perspectives on “Digital Mental Health—Breaking a Lance for Prevention.”
Psychological Field Versus Physiological Field: From Qualitative Analysis to Quantitative Modeling of the Mental Status
Welcome to the fifth issue of IEEE Transactions on Computational Social Systems (TCSS) in 2022. After the usual introduction of our 24 regular articles, we would like to discuss the topic of “Psychological Field Versus Physiological Field: From Qualitative Analysis to Quantitative Modelling of the Mental Status.”
Rethinking Auditory Affective Descriptors Through Zero-Shot Emotion Recognition in Speech
Zero-shot speech emotion recognition (SER) endows machines with the ability of sensing unseen-emotional states in speech, compared with conventional SER endeavors on supervised cases. On addressing the zero-shot SER task, auditory affective descriptors (AADs) are typically employed to transfer affective knowledge from seen- to unseen-emotional states. However, it remains unknown which types of AADs can well describe emotional states in speech dur…
Covid-19’s Impact on Mental Health—The Hour of Computational Aid
Welcome to the fourth issue of IEEE Transactions on Computational Social Systems (TCSS) in 2022. First, we have some exciting news to share. In late June, Clarivate updated the Impact Factor of all journals which are indexed by Web of Science. According to the Journal Citation Reports, the 2021 Journal Impact Factor of IEEE TCSS was 4.727. Many thanks to all for your great effort and support
A Review on Five Recent and Near-Future Developments in Computational Processing of Emotion in the Human Voice
We provide a short review on the recent and near-future developments of computational processing of emotion in the voice, highlighting (a) self-learning of representations moving continuously away from traditional expert-crafted or brute-forced feature representations to end-to-end learning, (b) a movement towards the coupling of analysis and synthesis of emotional voices to foster better mutual understanding, (c) weakly supervised learning at a …
The effect of music in anxiety reduction: A psychological and physiological assessment
Extensive research has been published on the effects of music in reducing anxiety. Yet, for most of the existing works, a common methodology regarding musical genres and measurement techniques is missing, which limits considerably the comparison between them. In this study, we assess, for the first time, markedly different musical genres with both psychological and physiological measurements. Three previously studied musical samples from differen…
Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development
Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child’s first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized. More recently, specific preverbal phenomena were discussed to play a role as early indicators of atypical devel…
Customized ViNeRS Method for Video Neuro-Advertising of Green Housing
The implementation of advertising for green housing usually involves consideration of individual differences among potential buyers, their desires for residential unit features as well as location impacts on a selected property. Much more rarely, there is consideration of the arousal and valence, affective behavior, emotional, and physiological states of possible buyers of green housing (AVABEPS) while they review the advertising. Yet, no integra…
The Interspeech 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity
The INTERSPEECH 2019 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Styrian Dialects Sub-Challenge, three types of Austrian-German dialects have to be classified; in the Continuous Sleepiness Sub-Challenge, the sleepiness of a speaker has to be assessed as regression problem; in the Baby Sound Sub-Challenge, five types of infant sounds ha…
Music Theoretic and Perception-based Features for Audio Key Determination
The musical key of a piece is the fundamental knowledge for many Music Information Retrieval tasks as automatic transcription, chord detection or automatic play list generation. To this end, novel features are proposed and evaluated on the basis of musical knowledge, in this article—a total of 13 feature groups based on chromatic representation include scales, chords, major and minor Probe Tone Ratings, and further derived variations. We present …
‘Mister D.J., Cheer Me Up!’: Musical and Textual Features for Automatic Mood Classification
Mass consumption of large collections of digital music asks for efficient and intuitive ways of organization. In this article, a system is presented which recognizes the evoked music mood on the basis of a wide variety of features, closely sticking to real world conditions. A two-dimensional mood model is discussed in which moods resemble binary values for arousal and valence and an easy and thus user-friendly method is presented through which a …
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‘Mister D.J., Cheer Me Up!’: Musical and Textual Features for Automatic Mood Classification
Mass consumption of large collections of digital music asks for efficient and intuitive ways of organization. In this article, a system is presented which recognizes the evoked music mood on the basis of a wide variety of features, closely sticking to real world conditions. A two-dimensional mood model is discussed in which moods resemble binary values for arousal and valence and an easy and thus user-friendly method is presented through which a …
Music Theoretic and Perception-based Features for Audio Key Determination
The musical key of a piece is the fundamental knowledge for many Music Information Retrieval tasks as automatic transcription, chord detection or automatic play list generation. To this end, novel features are proposed and evaluated on the basis of musical knowledge, in this article—a total of 13 feature groups based on chromatic representation include scales, chords, major and minor Probe Tone Ratings, and further derived variations. We present …
The Interspeech 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity
The INTERSPEECH 2019 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Styrian Dialects Sub-Challenge, three types of Austrian-German dialects have to be classified; in the Continuous Sleepiness Sub-Challenge, the sleepiness of a speaker has to be assessed as regression problem; in the Baby Sound Sub-Challenge, five types of infant sounds ha…
Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development
Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child’s first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized. More recently, specific preverbal phenomena were discussed to play a role as early indicators of atypical devel…
Customized ViNeRS Method for Video Neuro-Advertising of Green Housing
The implementation of advertising for green housing usually involves consideration of individual differences among potential buyers, their desires for residential unit features as well as location impacts on a selected property. Much more rarely, there is consideration of the arousal and valence, affective behavior, emotional, and physiological states of possible buyers of green housing (AVABEPS) while they review the advertising. Yet, no integra…
A Review on Five Recent and Near-Future Developments in Computational Processing of Emotion in the Human Voice
We provide a short review on the recent and near-future developments of computational processing of emotion in the voice, highlighting (a) self-learning of representations moving continuously away from traditional expert-crafted or brute-forced feature representations to end-to-end learning, (b) a movement towards the coupling of analysis and synthesis of emotional voices to foster better mutual understanding, (c) weakly supervised learning at a …
The effect of music in anxiety reduction: A psychological and physiological assessment
Extensive research has been published on the effects of music in reducing anxiety. Yet, for most of the existing works, a common methodology regarding musical genres and measurement techniques is missing, which limits considerably the comparison between them. In this study, we assess, for the first time, markedly different musical genres with both psychological and physiological measurements. Three previously studied musical samples from differen…
Digital Mental Health—Breaking a Lance for Prevention
Welcome to the last issue of IEEE Transactions On Computational Social Systems (TCSS) of 2022. In this issue, we publish a Special Issue on Advanced Cognitive Computing for Data-Driven Computational Social Systems, which includes 23 articles. Moreover, we also would like to share some of our opinions and perspectives on “Digital Mental Health—Breaking a Lance for Prevention.”
Psychological Field Versus Physiological Field: From Qualitative Analysis to Quantitative Modeling of the Mental Status
Welcome to the fifth issue of IEEE Transactions on Computational Social Systems (TCSS) in 2022. After the usual introduction of our 24 regular articles, we would like to discuss the topic of “Psychological Field Versus Physiological Field: From Qualitative Analysis to Quantitative Modelling of the Mental Status.”
Rethinking Auditory Affective Descriptors Through Zero-Shot Emotion Recognition in Speech
Zero-shot speech emotion recognition (SER) endows machines with the ability of sensing unseen-emotional states in speech, compared with conventional SER endeavors on supervised cases. On addressing the zero-shot SER task, auditory affective descriptors (AADs) are typically employed to transfer affective knowledge from seen- to unseen-emotional states. However, it remains unknown which types of AADs can well describe emotional states in speech dur…
Covid-19’s Impact on Mental Health—The Hour of Computational Aid
Welcome to the fourth issue of IEEE Transactions on Computational Social Systems (TCSS) in 2022. First, we have some exciting news to share. In late June, Clarivate updated the Impact Factor of all journals which are indexed by Web of Science. According to the Journal Citation Reports, the 2021 Journal Impact Factor of IEEE TCSS was 4.727. Many thanks to all for your great effort and support
Intelligent Music Intervention for Mental Disorders: Insights and Perspectives
Welcome to the first issue of IEEE Transactions on Computational Social Systems (TCSS) of 2023. The past 2022 was again a very productive year, in which we have published 159 articles with about 1850 pages in six issues. We also received much great and exciting news
Can a Holistic View Facilitate the Development of Intelligent Traditional Chinese Medicine? A Survey
Intelligent traditional Chinese medicine (ITCM) is an emerging interdisciplinary subject. It aims to efficiently and precisely promote the prevention and treatment of diseases and health management in Chinese medicine clinical practice via the combination of traditional Chinese medicine (TCM) fundamentals and artificial intelligence technologies. Presently, it is experiencing dramatic growth in recent years. On the one hand, a holistic view, as a…
The promise of digital healthcare technologies
Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthe…
Refashioning Emotion Recognition Modeling: The Advent of Generalized Large Models
After its inception, emotion recognition or affective computing has increasingly become an active research topic due to its broad applications. The corresponding computational models have gradually migrated from statistically shallow models to neural-network-based deep models, which can significantly boost the performance of emotion recognition and consistently achieve the best results on different benchmarks, and thus has been considered the fir…
Challenges in Observing the Emotions of Children with Autism Interacting with a Social Robot
This paper concerns the methodology of multi-modal data acquisition in observing emotions experienced by children with autism while they interact with a social robot. As robot-enhanced therapy gains more and more attention and proved to be effective in autism, such observations might influence the future development and use of such technologies. The paper is based on an observational study of child-robot interaction, during which multiple modalit…
Establishing the reliability of metrics extracted from long-form recordings using Lena and the Aclew pipeline
Long-form audio recordings are increasingly used to study individual variation, group differences, and many other topics in theoretical and applied fields of developmental science, particularly for the description of children's language input (typically speech from adults) and children's language output (ranging from babble to sentences). The proprietary LENA software has been available for over a decade, and with it, users have come to rely on d…
Creating Healthier Living Environments: The Role of Soundscapes in Promoting Mental Health and Well-Being
Quality in science communication with communicative artificial intelligence: A principle-based framework
The rapid advancement of communicative artificial intelligence (ComAI) is profoundly impacting science communication, offering new opportunities for easier and more audience-oriented communication. However, it also poses several challenges for its practice. Based on a narrative review of literature on science communication and ComAI quality, this article develops a framework of quality principles for science communication with ComAI. The framewor…
Bridging acute and chronic stress effects on inflammation: Protocol for a mixed-methods intensive longitudinal study
Acute stress triggers adaptive physiological responses-including transient increases in inflammatory cytokines-while chronic stress is associated with sustained inflammatory activity that may underlie the development of various disorders. Despite extensive research on each stress type individually, the transition and interaction between them remain underexplored. This study aims to address this gap by employing an intensive longitudinal measureme…
Guidelines for Emotion Recognition in Robot-Supported Interventions in Autism
Therapy for children with autism spectrum disorder benefits from the use of diverse technologies, as most children with the condition are eager to interact with them. The integration of emotion recognition technologies with social robots offers promising opportunities to make therapeutic interactions more adaptive, personalized, and responsive to a child’s emotional state, potentially improving engagement and learning outcomes. The purpose of thi…
Computer Science (17 works) · Psychology (17 works) · Data science (8 works) · Artificial Intelligence (7 works) · Cognitive psychology (6 works) · Cognitive science (5 works) · Developmental psychology (4 works) · Digital Mental Health Interventions (4 works) · Linguistics (4 works) · Medicine (4 works)