A 3-D Audio-Visual Corpus of Affective Communication

Communication between humans deeply relies on the capability of expressing and recognizing feelings. For this reason, research on human-machine interaction needs to focus on the recognition and simulation of emotional states, prerequisite of which is the collection of affective corpora. Currently available datasets still represent a bottleneck for the difficulties arising during the acquisition and labeling of affective data. In this work, we present a new audio-visual corpus for possibly the two most important modalities used by humans to communicate their emotional states, namely speech and facial expression in the form of dense dynamic 3-D face geometries. We acquire high-quality data by working in a controlled environment and resort to video clips to induce affective states. The annotation of the speech signal includes: transcription of the corpus text into the phonological representation, accurate phone segmentation, fundamental frequency extraction, and signal intensity estimatio...

• Type: Journal
• Year: 2010
• Where: TMM
• Authors: Gabriele Fanelli, Jürgen Gall, Harald Romsdorfer, Thibaut Weise, Luc J. Van Gool
• Keywords: Affective, Emotional States, Facial Expression, Management, TMM 2010