Summary of the paper
| Title | The AV-LASYN Database: a Synchronous Corpus of Audio and 3D Facial Marker Data for Audio-Visual Laughter Synthesis |
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| Authors | Huseyin Cakmak, Jerome Urbain, Thierry Dutoit and Joelle Tilmanne |
| Abstract | A synchronous database of acoustic and 3D facial marker data was built for audio-visual laughter synthesis. Since the aim is to use this database for HMM-based modeling and synthesis, the amount of collected data from one given subject had to be maximized. The corpus contains 251 utterances of laughter from one male participant. Laughter was elicited with the help of humorous videos. The resulting database is synchronous between modalities (audio and 3D facial motion capture data). Visual 3D data is available in common formats such as BVH and C3D with head motion and facial deformation independently available. Data is segmented and audio has been annotated. Phonetic transcriptions are available in the HTK-compatible format. Principal component analysis has been conducted on visual data and has shown that a dimensionality reduction might be relevant. The corpus may be obtained under a research license upon request to authors. |
| Topics | Emotion Recognition/Generation, Statistical and Machine Learning Methods |
Full paper  |
The AV-LASYN Database: a Synchronous Corpus of Audio and 3D Facial Marker Data for Audio-Visual Laughter Synthesis |
| Bibtex | @InProceedings{CAKMAK14.163, author = {Huseyin Cakmak and Jerome Urbain and Thierry Dutoit and Joelle Tilmanne}, title = {The AV-LASYN Database: a Synchronous Corpus of Audio and 3D Facial Marker Data for Audio-Visual Laughter Synthesis}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |