His primary areas of study are Speech recognition, Artificial intelligence, Natural language processing, Interview and Nonverbal communication. His Speech recognition research is multidisciplinary, relying on both Entropy, Discriminative model, Facial expression and Feature learning. His Artificial intelligence study often links to related topics such as Machine learning.
Stefan Scherer combines subjects such as Word, Speech technology and Perception with his study of Natural language processing. His studies in Nonverbal communication integrate themes in fields like Multimedia, Virtual reality, Human–computer interaction, Public speaking and Gesture. His Human–computer interaction study incorporates themes from Accommodation and Human communication.
His main research concerns Artificial intelligence, Speech recognition, Human–computer interaction, Cognitive psychology and Nonverbal communication. His Artificial intelligence research includes elements of Machine learning, Pattern recognition and Natural language processing. The various areas that Stefan Scherer examines in his Speech recognition study include Mixture model and Feature learning.
The concepts of his Human–computer interaction study are interwoven with issues in Multimedia, Facial expression and Human communication. He works mostly in the field of Cognitive psychology, limiting it down to concerns involving Depression and, occasionally, Affect, Clinical psychology, Mood and Speech production. His Nonverbal communication research is multidisciplinary, incorporating elements of Perception and Public speaking.
The scientist’s investigation covers issues in Artificial intelligence, Cognitive psychology, Speech recognition, Applied psychology and Facial expression. His Artificial intelligence research includes themes of Machine learning, Pattern recognition, Nonverbal communication and Natural language processing. As a part of the same scientific family, he mostly works in the field of Machine learning, focusing on Fusion and, on occasion, Depression.
His Nonverbal communication research focuses on subjects like Perplexity, which are linked to Affect. The various areas that Stefan Scherer examines in his Cognitive psychology study include Ensemble learning and Motivational interviewing. As a part of the same scientific study, Stefan Scherer usually deals with the Speech recognition, concentrating on Feature learning and frequently concerns with Generative grammar, Adversarial system, Discriminative model and Variation.
Stefan Scherer mainly investigates Artificial intelligence, Nonverbal communication, Affect, Natural language processing and Depression. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Multimedia and Job interview. His work on Nonverbal behavior as part of general Nonverbal communication research is often related to Suicidal risk and Public health, thus linking different fields of science.
His studies deal with areas such as Schizophrenia, Developmental psychology, Facial expression, Social cognition and Oxytocin as well as Affect. Stefan Scherer usually deals with Natural language processing and limits it to topics linked to Perception and Speech recognition. His research in Depression tackles topics such as Social psychology which are related to areas like Cognitive psychology.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A review of depression and suicide risk assessment using speech analysis
Nicholas Cummins;Stefan Scherer;Jarek Krajewski;Sebastian Schnieder.
Speech Communication (2015)
AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge
Michel Valstar;Jonathan Gratch;Björn Schuller;Fabien Ringeval.
acm multimedia (2016)
COVAREP — A collaborative voice analysis repository for speech technologies
Gilles Degottex;John Kane;Thomas Drugman;Tuomo Raitio.
international conference on acoustics, speech, and signal processing (2014)
SimSensei kiosk: a virtual human interviewer for healthcare decision support
David DeVault;Ron Artstein;Grace Benn;Teresa Dey.
adaptive agents and multi-agents systems (2014)
AVEC 2017: Real-life Depression, and Affect Recognition Workshop and Challenge
Fabien Ringeval;Björn Schuller;Michel Valstar;Jonathan Gratch.
acm multimedia (2017)
The Distress Analysis Interview Corpus of human and computer interviews
Jonathan Gratch;Ron Artstein;Gale Lucas;Giota stratou.
language resources and evaluation (2014)
Cicero - Towards a Multimodal Virtual Audience Platform for Public Speaking Training
Ligia Maria Batrinca;Giota Stratou;Ari Shapiro;Louis-Philippe Morency.
intelligent virtual agents (2013)
Multiple classifier systems for the classificatio of audio-visual emotional states
Michael Glodek;Stephan Tschechne;Georg Layher;Martin Schels.
affective computing and intelligent interaction (2011)
Automatic behavior descriptors for psychological disorder analysis
Stefan Scherer;Giota Stratou;Marwa Mahmoud;Jill Boberg.
ieee international conference on automatic face gesture recognition (2013)
Virtual character performance from speech
Stacy Marsella;Yuyu Xu;Margaux Lhommet;Andrew Feng.
symposium on computer animation (2013)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: