Imitating conversational laughter with an articulatory speech synthesizer

Abstract

In this study we present initial efforts to model laughter with an articulatory speech synthesizer. We aimed at imitating a real laugh taken from a spontaneous speech database and created several synthetic versions of it using articulatory synthesis and diphone synthesis. In modeling laughter with articulatory synthesis, we also approximated features like breathing noises that do not normally occur in speech. Evaluation with respect to the perceived degree of naturalness indicated that the laugh stimuli would pass as "laughs'; in an appropriate conversational context. In isolation, though, significant differences could be measured with regard to the degree of variation (durational patterning, fundamental frequency, intensity) within each laugh.