The MAHNOB Laughter database ?
Laughter is clearly an audiovisual event, consisting of the laughter vocalization and of facial activity, mainly around the mouth and sometimes in the upper face. A major obstacle in studying the audiovisual aspects of laughter is the lack of suitable data. For this reason, the majority of past research on laughter classification/detection has focused on audio-only approaches. A few audiovisual studies exist which use audiovisual data from existing corpora of recorded meetings. The main problem with such data is that they usually contain large head movements which make audiovisual analysis very difficult. In this work, we present a new publicly available audiovisual database, the MAHNOB Laughter database, suitable for studying laughter. It contains 22 subjects who were recorded while watching stimulus material, using two microphones, a video camera and a thermal camera. The primary goal was to elicit laughter, but in addition, posed smiles, posed laughter, and speech were recorded as well. In total, 180 sessions are available with a total duration of 3h and 49min. There are 563 laughter episodes, 849 speech utterances, 51 posed laughs, 67 speechlaughs episodes and 167 other vocalizations annotated in the database. We also report baseline experiments for audio, visual and audiovisual approaches for laughter-vs-speech discrimination as well as further experiments on discrimination between voiced laughter, unvoiced laughter and speech. These results suggest that the combination of audio and visual information is beneficial in the presence of acoustic noise and helps discriminating between voiced laughter episodes and speech utterances. Finally, we report preliminary experiments on laughter-vs-speech discrimination based on thermal images.
laughter database audiovisual thermal audiovisual automatic laughterspeech discrimination