A crowdsourcing based mobile image translation and knowledge sharing service

Abstract

Travelers in countries that use an unfamiliar script cannot use pocket translators or online translation services to understand menus, maps, signs and other important information, because they are unable to write the text they see. Solutions based on optical character recognition provide very limited performance in real-world situations and for complex scripts such as Chinese and Japanese. In this paper, we propose an alternative image translation solution based on crowdsourcing. A large number of human workers on mobile terminals are used to carry out the tasks of image recognition, translation and quality assurance. Compared to purely technical solutions, this human computation approach is also able to account for context and non-textual cues, and provide higher level information to the end-user. In this paper, we describe a preliminary user study to create a model of end-user requirements.