iHEARu-PLAY: Introducing a game for crowdsourced data collection for affective computing

• Published in: International Conference on Affective Computing and Intelligent Interaction and workshops pp. 891 - 897
• Main Authors: Hantke, Simone, Eyben, Florian, Appel, Tobias, Schuller, Bjorn
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.09.2015
• Subjects: Affective computing; annotation; Annotations; Artificial intelligence; Computation; Crowdsourcing; data collection; Games; gamification; Labeling; Labelling; Players; Speech; Tasks
• ISSN: 2156-8111
• DOI: 10.1109/ACII.2015.7344680

We introduce iHEARu-PLAY, a web-based multi-player game for crowdsourced database collection and - most important - labelling. Existing databases (with speech and video content) can be added to the game and labelling tasks can be defined via a web-interface. The primary purpose of iHEARu-PLAY is multi-label, holistic annotation of multi-modal affective speech databases. Players perform labelling (or prompted recording) tasks and are rewarded with scores and prizes, which are computed based on the "correctness" of their annotations, e.g., the agreement with a pre-defined gold standard or with the other players. iHEARu-PLAY is implemented with the open source high-level Python Web framework Django and can be installed on Unix and Windows platforms. Its modular architecture allows for easy integration of custom extensions: New gaming components can be added as plugins in order to support new databases and modalities. Label categories for each database are individually selectable and editable. Audio, image and video annotation are currently supported. iHEARu-PLAY will be available to the research community as a ready-to-use web-service. Researchers can add their own databases, optionally post rewards, and receive annotation results in the end. General users can register to play the game, have fun, compete with other players, and at the same time support science.