Empathy, as defined in behavioral sciences, expresses the ability of human beings to recognize, understand and react to emotions, attitudes and beliefs of others. In this paper, we address two related problems in automatic affective behavior analysis: the design of the annotation protocol and the automatic recognition of empathy from human–human dyadic spoken conversations. We propose and evaluate an annotation scheme for empathy inspired by the modal model of emotions. The annotation scheme was evaluated on a corpus of real-life, dyadic spoken conversations. In the context of behavioral analysis, we designed an automatic segmentation and classification system for empathy. Given the different speech and language levels of representation where empathy may be communicated, we investigated features derived from the lexical and acoustic spaces. The feature development process was designed to support both the fusion and automatic selection of relevant features from a high dimensional space. The automatic classification system was evaluated on call center conversations where it showed significantly better performance than the baseline. © 2017 Elsevier Ltd. All rights reserved.

Annotating and Modeling Empathy in Spoken Conversations / Alam, Firoj; Danieli, Morena; Riccardi, Giuseppe. - In: COMPUTER SPEECH AND LANGUAGE. - ISSN 0885-2308. - ELETTRONICO. - 50:(2018), pp. 40-61. [10.1016/j.csl.2017.12.003]

Annotating and Modeling Empathy in Spoken Conversations

Firoj Alam;Morena Danieli;Giuseppe Riccardi
2018-01-01

Abstract

Empathy, as defined in behavioral sciences, expresses the ability of human beings to recognize, understand and react to emotions, attitudes and beliefs of others. In this paper, we address two related problems in automatic affective behavior analysis: the design of the annotation protocol and the automatic recognition of empathy from human–human dyadic spoken conversations. We propose and evaluate an annotation scheme for empathy inspired by the modal model of emotions. The annotation scheme was evaluated on a corpus of real-life, dyadic spoken conversations. In the context of behavioral analysis, we designed an automatic segmentation and classification system for empathy. Given the different speech and language levels of representation where empathy may be communicated, we investigated features derived from the lexical and acoustic spaces. The feature development process was designed to support both the fusion and automatic selection of relevant features from a high dimensional space. The automatic classification system was evaluated on call center conversations where it showed significantly better performance than the baseline. © 2017 Elsevier Ltd. All rights reserved.
2018
Alam, Firoj; Danieli, Morena; Riccardi, Giuseppe
Annotating and Modeling Empathy in Spoken Conversations / Alam, Firoj; Danieli, Morena; Riccardi, Giuseppe. - In: COMPUTER SPEECH AND LANGUAGE. - ISSN 0885-2308. - ELETTRONICO. - 50:(2018), pp. 40-61. [10.1016/j.csl.2017.12.003]
File in questo prodotto:
File Dimensione Formato  
CSL18-AModelingEmpathy.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 689.91 kB
Formato Adobe PDF
689.91 kB Adobe PDF   Visualizza/Apri
1705.04839.pdf

accesso aperto

Tipologia: Pre-print non referato (Non-refereed preprint)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 823.38 kB
Formato Adobe PDF
823.38 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/199916
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 45
  • ???jsp.display-item.citation.isi??? 32
social impact