S
Sebastian Möller
Researcher at Technical University of Berlin
Publications - 531
Citations - 7103
Sebastian Möller is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Quality (business) & Quality of experience. The author has an hindex of 34, co-authored 491 publications receiving 5830 citations. Previous affiliations of Sebastian Möller include German Research Centre for Artificial Intelligence & University of Oslo.
Papers
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Proceedings ArticleDOI
Application of Just-Noticeable Difference in Quality as Environment Suitability Test for Crowdsourcing Speech Quality Assessment Task
Babak Naderi,Sebastian Möller +1 more
TL;DR: A new Just Noticeable Difference of Quality (JNDQ) test is proposed as a remote screening method for assessing the suitability of the work environment for participating in speech quality assessment tasks and a minimum threshold is proposed for this test.
Proceedings Article
Crowdee: mobile crowdsourcing micro-task platform for celebrating the diversity of languages.
TL;DR: A novel crowdsourcing platform that operates on mobile devices and makes data generation and labeling scenarios available for many related research tracks potentially covering also small and underrepresented languages is provided to the community.
Journal ArticleDOI
Development of a reactance scale for human–computer interaction
TL;DR: In this article, the authors describe the development and validation of the reactance scale for human-computer interaction (RSHCI), which is designed to measure state reactance in the context of HCI research and is the first questionnaire to address the topic in this context.
Proceedings ArticleDOI
Preliminary findings on image preference characterization based on neurophysiological signal analysis: Towards objective QoE modeling
TL;DR: This pilot study explores the use of neurophysiological signals as correlates of image preference characterization and results have shown promising results and mental states associated with preferred and non-preferred images, as well as baseline neutral state could be classified with above-chance levels.
Proceedings ArticleDOI
Parameter-based prediction of speech quality in listening context—Towards a WB E-model
TL;DR: A first version of a wideband E-model applicable to planning future telephone networks in a listening-only context that allows to predict wideband speech quality under bandwidth restrictions and wideband and narrowband speech coding with and without transmission errors, including the quality impact due to noise.