TY - GEN
T1 - Introducing an emotion-driven assistance system for cognitively impaired individuals
AU - Hantke, Simone
AU - Cohrs, Christian
AU - Schmitt, Maximilian
AU - Tannert, Benjamin
AU - Lütkebohmert, Florian
AU - Detmers, Mathias
AU - Schelhowe, Heidi
AU - Schuller, Björn
N1 - Publisher Copyright:
© The Author(s) 2018.
PY - 2018
Y1 - 2018
N2 - Mental, neurological and/or physical disabilities often affect individuals’ cognitive processes, which in turn can introduce difficulties with remembering what they have learnt. Therefore, completing trivial daily tasks can be challenging and supervision or help from others is constantly needed. In this regard, these individuals with special needs can benefit from nowadays advanced assistance techniques. Within this contribution, a language-driven, workplace integrated, assistance system is being proposed, supporting disabled individuals in the handling of certain activities while taking into account their emotional-cognitive constitution and state. In this context, we present a set of baseline results for emotion recognition tasks and conduct machine learning experiments to benchmark the performance of an automatic emotion recognition system on the collected data. We show that this is a challenging task that can nevertheless be tackled with state-of-the-art methodologies.
AB - Mental, neurological and/or physical disabilities often affect individuals’ cognitive processes, which in turn can introduce difficulties with remembering what they have learnt. Therefore, completing trivial daily tasks can be challenging and supervision or help from others is constantly needed. In this regard, these individuals with special needs can benefit from nowadays advanced assistance techniques. Within this contribution, a language-driven, workplace integrated, assistance system is being proposed, supporting disabled individuals in the handling of certain activities while taking into account their emotional-cognitive constitution and state. In this context, we present a set of baseline results for emotion recognition tasks and conduct machine learning experiments to benchmark the performance of an automatic emotion recognition system on the collected data. We show that this is a challenging task that can nevertheless be tackled with state-of-the-art methodologies.
KW - Affect
KW - Disabilities
KW - Speech and emotion recognition
KW - Speech-driven assistive technology
UR - http://www.scopus.com/inward/record.url?scp=85049788959&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-94277-3_75
DO - 10.1007/978-3-319-94277-3_75
M3 - Conference contribution
AN - SCOPUS:85049788959
SN - 9783319942766
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 486
EP - 494
BT - Computers Helping People with Special Needs - 16th International Conference, ICCHP 2018, Proceedings
A2 - Miesenberger, Klaus
A2 - Kouroupetroglou, Georgios
PB - Springer Verlag
T2 - 16th International Conference on Computers Helping People with Special Needs, ICCHP 2018
Y2 - 11 July 2018 through 13 July 2018
ER -