Thurid Vogt
Papers
5
Total Citations
491
H-Index
5
About
Thurid Vogt is a leading researcher in affective computing and human-robot interaction, whose work has fundamentally advanced how machines recognize and respond to human emotional states. Her research centers on automatic emotion recognition from speech and multimodal cues, with a particular focus on developing robust classification systems for real-world human-machine interaction. Vogt's most influential contribution is her systematic investigation of acoustic and linguistic features for emotional state classification, as demonstrated in her highly cited 2007 paper (189 citations) on low-level descriptors and functionals, where she and collaborators analyzed 4,244 features to classify emotional user states in children interacting with a pet robot. Her 2010 work "Whodunnit" (146 citations) further refined this approach by identifying the most salient feature types for emotion detection. Vogt also made notable contributions to human-robot interaction through her 2006 study on empathic android robots (96 citations), which explored equipping robots with perceptual capabilities for assessing human affective evaluations. Her research has been instrumental in demonstrating that effective emotion recognition requires careful selection of both acoustic and linguistic features, and her work on prototype-based classification methods has provided a theoretical framework for understanding emotional expression in interactive contexts.
Research Focus
Key Achievements
Top Papers
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- 4Patterns, prototypes, performance: classifying emotional user states41 citations · 2008
- 5Evaluation and Discussion of Multi-modal Emotion Recognition19 citations · 2009