In this paper, we explore the possibility of building a model of subject arousal by exploiting the acquisition and the analysis of speech and electrodermal activity (EDA). Several issues have to be addressed to reach this goal as the estimation of the relationship between arousal and behavioral measures and the reliability of EDA signal during speech production. To accomplish this task, we will investigate the relation among EDA, speech activity and subject arousal, during isolated affective word pronunciation. Our results show that significant information on subject arousal can be obtained by analyzing EDA during the processing of out-of-context words with an emotional content in a reading aloud task. Based on a sample of eighteen Italian participants, we observed a significant relation between EDA features and self-reported arousal scores. Quantitative models relating EDA andspeech-derived features are proposed and discussed. We found that increasing values of tonic and phasic components of EDA signals correspond to increasing self-assessed arousal scores; Mel-frequency cepstral analysis of speech was also shown to carry relevant information about subject arousal, with a significant inverse relation to self-assessed scores. Our results suggest how the analysis of concurrent acquisition of EDA and speech featuresmay offer a valid approach for the prediction of subject arousal during speech production, as well as a method for validating self-assessment ratings themselves.

Towards a model of arousal change after affective word pronunciation based on electrodermal activity and speech analysis

Marzi C
Primo
;
2021

Abstract

In this paper, we explore the possibility of building a model of subject arousal by exploiting the acquisition and the analysis of speech and electrodermal activity (EDA). Several issues have to be addressed to reach this goal as the estimation of the relationship between arousal and behavioral measures and the reliability of EDA signal during speech production. To accomplish this task, we will investigate the relation among EDA, speech activity and subject arousal, during isolated affective word pronunciation. Our results show that significant information on subject arousal can be obtained by analyzing EDA during the processing of out-of-context words with an emotional content in a reading aloud task. Based on a sample of eighteen Italian participants, we observed a significant relation between EDA features and self-reported arousal scores. Quantitative models relating EDA andspeech-derived features are proposed and discussed. We found that increasing values of tonic and phasic components of EDA signals correspond to increasing self-assessed arousal scores; Mel-frequency cepstral analysis of speech was also shown to carry relevant information about subject arousal, with a significant inverse relation to self-assessed scores. Our results suggest how the analysis of concurrent acquisition of EDA and speech featuresmay offer a valid approach for the prediction of subject arousal during speech production, as well as a method for validating self-assessment ratings themselves.
Campo DC Valore Lingua
dc.authority.ancejournal BIOMEDICAL SIGNAL PROCESSING AND CONTROL en
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC en
dc.authority.people Marzi C en
dc.authority.people Greco A en
dc.authority.people Scilingo EP en
dc.authority.people Vanello N en
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dc.date.accessioned 2024/02/19 08:34:19 -
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dc.date.firstsubmission 2024/09/25 17:04:12 *
dc.date.issued 2021 -
dc.date.submission 2024/09/25 17:04:12 *
dc.description.abstracteng In this paper, we explore the possibility of building a model of subject arousal by exploiting the acquisition and the analysis of speech and electrodermal activity (EDA). Several issues have to be addressed to reach this goal as the estimation of the relationship between arousal and behavioral measures and the reliability of EDA signal during speech production. To accomplish this task, we will investigate the relation among EDA, speech activity and subject arousal, during isolated affective word pronunciation. Our results show that significant information on subject arousal can be obtained by analyzing EDA during the processing of out-of-context words with an emotional content in a reading aloud task. Based on a sample of eighteen Italian participants, we observed a significant relation between EDA features and self-reported arousal scores. Quantitative models relating EDA andspeech-derived features are proposed and discussed. We found that increasing values of tonic and phasic components of EDA signals correspond to increasing self-assessed arousal scores; Mel-frequency cepstral analysis of speech was also shown to carry relevant information about subject arousal, with a significant inverse relation to self-assessed scores. Our results suggest how the analysis of concurrent acquisition of EDA and speech featuresmay offer a valid approach for the prediction of subject arousal during speech production, as well as a method for validating self-assessment ratings themselves. -
dc.description.affiliations Istituto di Linguistica Computazionale, CNR; Dipartimento di Ingegneria dell'informazione, UNIPI; Centro di Ricerca "Piaggio" -
dc.description.allpeople Marzi, C; Greco, A; Scilingo, Ep; Vanello, N -
dc.description.allpeopleoriginal Marzi C., Greco A., Scilingo E.P., Vanello N. en
dc.description.fulltext open en
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dc.identifier.doi 10.1016/j.bspc.2021.102517 en
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dc.relation.issue 102517 en
dc.relation.lastpage 8 en
dc.relation.medium ELETTRONICO en
dc.relation.numberofpages 8 en
dc.relation.volume 67 en
dc.subject.keywordseng speech -
dc.subject.keywordseng electrodermal activity -
dc.subject.keywordseng statistical models -
dc.subject.keywordseng arousal -
dc.subject.keywordseng word pronunciation -
dc.subject.singlekeyword speech *
dc.subject.singlekeyword electrodermal activity *
dc.subject.singlekeyword statistical models *
dc.subject.singlekeyword arousal *
dc.subject.singlekeyword word pronunciation *
dc.title Towards a model of arousal change after affective word pronunciation based on electrodermal activity and speech analysis en
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dc.type.referee Sì, ma tipo non specificato en
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scopus.contributor.affiliation National Research Council of Italy -
scopus.contributor.affiliation University of Pisa -
scopus.contributor.affiliation University of Pisa -
scopus.contributor.affiliation University of Pisa -
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scopus.contributor.country Italy -
scopus.contributor.country Italy -
scopus.contributor.country Italy -
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scopus.contributor.dptid 117058300 -
scopus.contributor.name Claudia -
scopus.contributor.name Alberto -
scopus.contributor.name Enzo Pasquale -
scopus.contributor.name Nicola -
scopus.contributor.subaffiliation Institute for Computational Linguistics; -
scopus.contributor.subaffiliation Dipartimento di Ingegneria dell'Informazione and Research Center “E. Piaggio”; -
scopus.contributor.subaffiliation Dipartimento di Ingegneria dell'Informazione and Research Center “E. Piaggio”; -
scopus.contributor.subaffiliation Dipartimento di Ingegneria dell'Informazione and Research Center “E. Piaggio”; -
scopus.contributor.surname Marzi -
scopus.contributor.surname Greco -
scopus.contributor.surname Scilingo -
scopus.contributor.surname Vanello -
scopus.date.issued 2021 *
scopus.description.abstracteng In this paper, we explore the possibility of building a model of subject arousal by exploiting the acquisition and the analysis of speech and electrodermal activity (EDA). Several issues have to be addressed to reach this goal as the estimation of the relationship between arousal and behavioral measures and the reliability of EDA signal during speech production. To accomplish this task, we will investigate the relation among EDA, speech activity and subject arousal, during isolated affective word pronunciation. Our results show that significant information on subject arousal can be obtained by analyzing EDA during the processing of out-of-context words with an emotional content in a reading aloud task. Based on a sample of eighteen Italian participants, we observed a significant relation between EDA features and self-reported arousal scores. Quantitative models relating EDA- and speech-derived features are proposed and discussed. We found that increasing values of tonic and phasic components of EDA signals correspond to increasing self-assessed arousal scores; Mel-frequency cepstral analysis of speech was also shown to carry relevant information about subject arousal, with a significant inverse relation to self-assessed scores. Our results suggest how the analysis of concurrent acquisition of EDA and speech features may offer a valid approach for the prediction of subject arousal during speech production, as well as a method for validating self-assessment ratings themselves. *
scopus.description.allpeopleoriginal Marzi C.; Greco A.; Scilingo E.P.; Vanello N. *
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scopus.identifier.doi 10.1016/j.bspc.2021.102517 *
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scopus.subject.keywords Arousal; Electrodermal activity; Speech; Statistical models; Word pronunciation; *
scopus.title Towards a model of arousal change after affective word pronunciation based on electrodermal activity and speech analysis *
scopus.titleeng Towards a model of arousal change after affective word pronunciation based on electrodermal activity and speech analysis *
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