NoXi

For the purpose of the MultiMediate challenge, we will provide a version of the NoXi dataset that contains video recordings, audio recordings and annotations.

Download: Please download the EULA here and send to the address below. We will then give you the link to access the dataset and annotations.

Contact: Daksitha Withanage Don,

The data is only to be used for non-commercial scientific purposes. If you use this dataset in a scientific publication, please cite the following papers:

1. 

   The NoXi Database: Multimodal Recordings of Mediated Novice-Expert Interactions

   Angelo Cafaro, Johannes Wagner, Tobias Baur, Soumia Dermouche, Mercedes Torres Torres, Catherine Pelachaud, Elisabeth André, Michel Valstar

   Proceedings of 19th ACM International Conference on Multimodal Interaction, pp. 350–359, 2017.

   Abstract Links BibTeX

   We present a novel multi-lingual database of natural dyadic novice- expert interactions, named NoXi, featuring screen-mediated dyadic human interactions in the context of information exchange and retrieval. NoXi is designed to provide spontaneous interactions with emphasis on adaptive behaviors and unexpected situations (e.g. conversational interruptions). A rich set of audio-visual data, as well as continuous and discrete annotations are publicly available through a web interface. Descriptors include low level social signals (e.g. gestures, smiles), functional descriptors (e.g. turn-taking, dialogue acts) and interaction descriptors (e.g. engagement, interest, and fluidity).

   doi: 10.1145/3136755.3136780

   Paper: cafaro17_icmi.pdf

   @inproceedings{cafaro17_icmi, title = {The NoXi Database: Multimodal Recordings of Mediated Novice-Expert Interactions}, author = {Cafaro, Angelo and Wagner, Johannes and Baur, Tobias and Dermouche, Soumia and Torres, Mercedes Torres and Pelachaud, Catherine and André, Elisabeth and Valstar, Michel}, year = {2017}, booktitle = {Proceedings of 19th ACM International Conference on Multimodal Interaction}, doi = {10.1145/3136755.3136780}, pages = {350–359} }