TY - GEN
T1 - A crowdsourcing based mobile image translation and knowledge sharing service
AU - Liu, Yefeng
AU - Lehdonvirta, Vili
AU - Kleppe, Mieke
AU - Alexandrova, Todorka
AU - Kimura, Hiroaki
AU - Nakajima, Tatsuo
N1 - Publisher Copyright:
© 2010 ACM.
PY - 2010/12/1
Y1 - 2010/12/1
N2 - 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.
AB - 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.
KW - crowdsourcing
KW - human computation
KW - image-Text recognition
KW - knowledge sharing
KW - mobile image translation
UR - http://www.scopus.com/inward/record.url?scp=85134713899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134713899&partnerID=8YFLogxK
U2 - 10.1145/1899475.1899481
DO - 10.1145/1899475.1899481
M3 - Conference contribution
AN - SCOPUS:85134713899
T3 - ACM International Conference Proceeding Series
BT - MUM 2010 - Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia
PB - Association for Computing Machinery
T2 - 9h International Conference on Mobile and Ubiquitous Multimedia, MUM 2010
Y2 - 1 December 2010 through 3 December 2010
ER -