Audio-visual Laughter Synthesis System

نویسندگان

  • Hüseyin Çakmak
  • Kevin El Haddad
  • Thierry Dutoit
چکیده

In this paper we propose an overview of a project aiming at building an audio-visual laughter synthesis system. The same approach is followed for acoustic and visual synthesis. First a database has been built to have synchronous audio and 3D visual landmarks tracking data. Then this data has been used to build HMM models of acoustic laughter and visual laughter separately. Visual laughter modeling was further separated into a facial modeling and head motion modeling. An automatic laughter segmentation process has been used to annotate visual laughter. Finally, simple rules were defined to synchronize all the different modalities to be able to produce new durations.

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تاریخ انتشار 2015