Consiglio Nazionale delle Ricerche

Tipo di prodottoContributo in atti di convegno
TitoloCombining Electrodermal Activity and Speech Analysis towards a more Accurate Emotion Recognition System
Anno di pubblicazione2019
FormatoElettronico
Autore/iGreco A., Marzi C., Lanata A., Scilingo E.P., Vanello N.
Affiliazioni autoriFaculty of Engineering - University of Pisa, Institute for Computational Linguistics - CNR, Faculty of Engineering - University of Pisa, Faculty of Engineering - University of Pisa, Faculty of Engineering - University of Pisa
Autori CNR e affiliazioni
  • CLAUDIA MARZI
Lingua/e
  • inglese
AbstractCurrent 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 to improve 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.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da229
Pagine a232
Pagine totali-
RivistaConference proceedings (IEEE Eng. Med. Biol. Soc., Conf.)
Attiva dal 2004
Editore: IEEE Service Center, - Piscataway, NJ
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1557-170X
Titolo chiave: Conference proceedings (IEEE Eng. Med. Biol. Soc., Conf.)
Titolo proprio: Conference proceedings : (IEEE Eng. Med. Biol. Soc., Conf.)
Titolo abbreviato: Conf. proc. (IEEE Eng. Med. Biol. Soc., Conf.)
Titoli alternativi:
  • IEEE Engineering in Medicine and Biology ... Annual Conference (IEEE Eng. Med. Biol. Soc., Conf.)
  • Proceedings of the ... Annual International Conference of the IEEE EMBS (IEEE Eng. Med. Biol. Soc., Conf.)
Numero volume della rivista41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Serie/Collana-
Titolo del volume-
Numero volume della serie/collana-
Curatore/i del volume-
ISBN978-1-5386-1311-5
DOI10.1109/EMBC.2019.8857745
Editore-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • INSPEC (Codice:19045145)
  • PubMed (Codice:https://www.ncbi.nlm.nih.gov/pubmed/31945884)
  • Scopus (Codice:2-s2.0-85077864872)
Parole chiaveemotion 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
Link (URL, URI)http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8857745&isnumber=8856280
Titolo convegno/congresso41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Luogo convegno/congressoBerlin, Germany
Data/e convegno/congresso23-27 July 20
RilevanzaInternazionale
RelazioneContributo
Titolo parallelo-
Note/Altre informazioni-
Strutture CNR
  • ILC — Istituto di linguistica computazionale "Antonio Zampolli"
Moduli/Attività/Sottoprogetti CNR
  • DUS.AD016.007.001 : Approcci interdisciplinari a modelli teorici e computazionali di acquisizione lessicale in contesti mono- e multi-lingui
  • DUS.AD016.075.004 : Modelli (bio-)computazionali dell'uso linguistico
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