DAIC-WOZ Database Description
This database is part of a larger corpus, the Distress Analysis Interview Corpus (DAIC) (Gratch et al.,2014), that contains clinical interviews designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder. These interviews were collected as part of a larger effort to create a computer agent that interviews people and identifies verbal and nonverbal indicators of mental illness (DeVault et al., 2014). Data collected include audio and video recordings and extensive questionnaire responses; this part of the corpus includes the Wizard-of-Oz interviews, conducted by an animated virtual interviewer called Ellie, controlled by a human interviewer in another room. Data has been transcribed and annotated for a variety of verbal and non-verbal features.
This share includes 189 sessions of interactions ranging between 7-33min (with an average of 16min). Each session includes transcript of the interaction, participant audio files, and facial features. For more details please refer to the documentation.
To be able to download the DAIC-WOZ database, please download, sign and return the agreement form to this e-mail address. Please note that, unfortunately, due to consent constraints we are only allowed to distribute the data to academics and other non-profit researchers. Please use your academic e-mail address when requesting the data download.
Gratch J, Artstein R, Lucas GM, Stratou G, Scherer S, Nazarian A, Wood R, Boberg J, DeVault D, Marsella S, Traum DR. The Distress Analysis Interview Corpus of human and computer interviews. InLREC 2014 May (pp. 3123-3128)
DeVault, D., Artstein, R., Benn, G., Dey, T., Fast, E., Gainer, A., Georgila, K., Gratch, J., Hartholt, A., Lhommet, M., Lucas, G., Marsella, S., Morbini, F., Nazarian, A., Scherer, S., Stratou, G., Suri, A., Traum, D., Wood, R., Xu, Y., Rizzo, A., and Morency, L.-P. (2014). “SimSensei kiosk: A virtual human interviewer for healthcare decision support”. In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’14), Paris