Title
Arousal And Valence Prediction In Spontaneous Emotional Speech: Felt Versus Perceived Emotion
Abstract
In this paper, we describe emotion recognition experiments carried out for spontaneous affective speech with the aim to compare the added value of annotation of felt emotion versus annotation of perceived emotion. Using speech material available in the TNO-GAMING corpus (a corpus containing audiovisual recordings of people playing videogames), speech-based affect recognizers were developed that can predict Arousal and Valence scalar values. Two types of recognizers were developed in parallel: one trained with felt emotion annotations (generated by the gamers themselves) and one trained with perceived/observed emotion annotations (generated by a group of observers). The experiments showed that, in speech, with the methods and features currently used, observed emotions are easier to predict than felt emotions. The results suggest that recognition performance strongly depends on how and by whom the emotion annotations arc carried out.
Year
Venue
Keywords
2009
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5
emotion, emotional speech database, emotion recognition
Field
DocType
Citations 
Arousal,Annotation,Emotion recognition,Computer science,Speech recognition
Conference
10
PageRank 
References 
Authors
0.66
7
6
Name
Order
Citations
PageRank
Khiet P. Truong130232.64
Khiet P. Truong230232.64
David A. van Leeuwen363159.01
Mark A. Neerincx475796.80
David A. van Leeuwen5363.60
Mark A. Neerincx6181.64