2026-05-15T14:03:40Zhttps://iris.cnr.it/oai/requestoai:iris.cnr.it:20.500.14243/3762892025-06-15T00:32:32Zcom_20.500.14243_46com_20.500.14243_21col_20.500.14243_47ou_ou239
Combining Electrodermal Activity and Speech Analysis towards a more Accurate Emotion Recognition System
Greco A
Marzi C
Lanata A
Scilingo EP
Vanello N
Greco, A
Marzi, C
Lanata, A
Scilingo, Ep
Vanello, N
emotion recognition
feature selection
pattern classification
physiology
psychology
support vector machines
human arousal level
single affective words
EDA
electrodermal activity
speech analysis
emotion recognition system
speech processing
Current research in the emotion recognition field is exploring the possibility of merging the information from physiological signals, behavioural data, and speech. Electrodermal activity (EDA) is amongst the main psychophysiological arousal indicators. Nonetheless, it is quite difficult to be analyzed in ecological scenarios, like, for instance, when the subject is speaking. On the other hand, speech carries relevant information of subject emotional state and its potential in the field of affective computing is still to be fully exploited. In this work, we aim at exploring the possibility of merging the information from electrodermal activity (EDA) and speech toimprove the recognition of human arousal level during the pronunciation of single affective words. Unlike the majority of studies in the literature, we focus on speakers' arousal rather than the emotion conveyed by the spoken word. Specifically, a support vector machine with recursive feature elimination strategy (SVM-RFE) is trained and tested on three datasets, i.e. using the two channels (i.e., speech and EDA) separately and then jointly. The results show that the merging of EDA and speech information significantly improves the marginal classifier (+11.64%). The six selected features by the RFE procedure will be used for the development of a future multivariate model of emotions.
2019
info:eu-repo/semantics/conferenceObject
https://hdl.handle.net/20.500.14243/376289
10.1109/EMBC.2019.8857745
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85077864872
info:eu-repo/semantics/altIdentifier/isbn/978-1-5386-1311-5
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8857745&isnumber=8856280
info:eu-repo/semantics/altIdentifier/wos/WOS:000557295300054
eng
ispartofbook:Proceedings on the IEEE Engineering in medicine and biology annual conference
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
volume:41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
firstpage:229
lastpage:232
numberofpages:4
serie:IEEE ENGINEERING IN MEDICINE AND BIOLOGY ... ANNUAL CONFERENCE PROCEEDINGS
ELETTRONICO