LAUGHTER DETECTION FOR ON-LINE HUMAN-ROBOT INTERACTION

Marie Tahon (1) , Laurence Devillers (1)

1 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur

This paper presents a study of laugh classification using a cross-corpus protocol. It aims at the automatic detection of laughs in a real-time human-machine interaction. Positive and negative laughs are tested with different classification tasks and different acoustic feature sets. F.measure results show an improvement on positive laughs classification from 59.5% to 64.5% and negative laughs recognition from 10.3% to 28.5%. In the context of the Chist-Era JOKER project, positive and negative laugh detection drives the policies of the robot Nao. A measure of engagement will be provided using also the number of positive laughs detected during the interaction.

Mots clés: Laughter detection; acoustic features; laughter emotional valence

Domaines: Intelligence artificielle [cs.AI]; Interface homme-machine [cs.HC]; Traitement du signal et de l'image [eess.SP]

Marie Tahon, Laurence Devillers. LAUGHTER DETECTION FOR ON-LINE HUMAN-ROBOT INTERACTION. Interdisciplinary Workshop on Laughter and Non-verbal Vocalisations in Speech, Apr 2015, Enschede, Netherlands. ⟨hal-02308884⟩