Automatic Motherese Detection for Face-to-Face Interaction Analysis

This paper deals with emotional speech detection in home movies. In this study, we focus on infant-directed speech also called "motherese" which is characterized by higher pitch, slower tempo, and exaggerated intonation. In this work, we show the robustness of approaches to automatic discrimination between infant-directed speech and normal directed speech. Specifically, we estimate the generalization capability of two feature extraction schemes extracted from supra-segmental and segmental information. In addition, two machine learning approaches are considered: k-nearest neighbors (k-NN) and Gaussian mixture models (GMM). Evaluations are carried out on real-life databases: home movies of the first year of an infant.

• Type: Conference
• Year: 2008
• Where: COST
• Authors: Ammar Mahdhaoui, Mohamed Chetouani, Cong Zong, Raquel Sofia Cassel, Catherine Saint-Georges, Marie-Christine Laznik, Sandra Maestro, Fabio Apicella, Filippo Muratori, David Cohen
• Keywords: COST 2008, Emotional Speech Detection, Home Movies, Infant-directed Speech, Multimedia