Personal Narrative (PN) is the recollection of individuals’ life experiences, events, and thoughts along with the associated emotions in the form of a story. Compared to other genres such as social media texts or microblogs, where people write about experienced events or products, the spoken PNs are complex to analyze and understand. They are usually long and unstructured, involving multiple and related events, characters as well as thoughts and emotions associated with events, objects, and persons. In spoken PNs, emotions are conveyed by changing the speech signal characteristics as well as the lexical content of the narrative. In this work, we annotate a corpus of spoken personal narratives, with the emotion valence using discrete values. The PNs are segmented into speech segments, and the annotators annotate them in the discourse context, with values on a 5 point bipolar scale ranging from -2 to +2 (0 for neutral). In this way, we capture the unfolding of the PNs events and changes in the emotional state of the narrator. We perform an in-depth analysis of the inter-annotator agreement, the relation between the label distribution w.r.t. the stimulus (positive/negative) used for the elicitation of the narrative, and compare the segment-level annotations to a baseline continuous annotation. We find that the neutral score plays an important role in the agreement. We observe that it is easy to differentiate the positive from the negative valence while the confusion with the neutral label is high.

Annotation of Valence for Spoken Personal Narratives / Tammewar, A.; Bayerl, P. S.; Braun, F.; Riedhammer, K.; Riccardi, G.. - (2022), pp. 7004-7013. (Intervento presentato al convegno LREC tenutosi a Marsiglia nel 20th - 25th June 2022).

Annotation of Valence for Spoken Personal Narratives

Tammewar A.;Riccardi G.
2022-01-01

Abstract

Personal Narrative (PN) is the recollection of individuals’ life experiences, events, and thoughts along with the associated emotions in the form of a story. Compared to other genres such as social media texts or microblogs, where people write about experienced events or products, the spoken PNs are complex to analyze and understand. They are usually long and unstructured, involving multiple and related events, characters as well as thoughts and emotions associated with events, objects, and persons. In spoken PNs, emotions are conveyed by changing the speech signal characteristics as well as the lexical content of the narrative. In this work, we annotate a corpus of spoken personal narratives, with the emotion valence using discrete values. The PNs are segmented into speech segments, and the annotators annotate them in the discourse context, with values on a 5 point bipolar scale ranging from -2 to +2 (0 for neutral). In this way, we capture the unfolding of the PNs events and changes in the emotional state of the narrator. We perform an in-depth analysis of the inter-annotator agreement, the relation between the label distribution w.r.t. the stimulus (positive/negative) used for the elicitation of the narrative, and compare the segment-level annotations to a baseline continuous annotation. We find that the neutral score plays an important role in the agreement. We observe that it is easy to differentiate the positive from the negative valence while the confusion with the neutral label is high.
2022
ELRA
Marsiglia
ELRA
979-10-95546-72-6
Tammewar, A.; Bayerl, P. S.; Braun, F.; Riedhammer, K.; Riccardi, G.
Annotation of Valence for Spoken Personal Narratives / Tammewar, A.; Bayerl, P. S.; Braun, F.; Riedhammer, K.; Riccardi, G.. - (2022), pp. 7004-7013. (Intervento presentato al convegno LREC tenutosi a Marsiglia nel 20th - 25th June 2022).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/340468
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