A crowdsourcing based mobile image translation and knowledge sharing service

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 limite...

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Bibliographic Details
Main Authors: Liu, Y, Lehdonvirta, V, Kleppe, M, Alexandrova, T, Kimura, H, Nakajima, T
Format: Conference item
Published: Association for Computing Machinery 2010
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author Liu, Y
Lehdonvirta, V
Kleppe, M
Alexandrova, T
Kimura, H
Nakajima, T
author_facet Liu, Y
Lehdonvirta, V
Kleppe, M
Alexandrova, T
Kimura, H
Nakajima, T
author_sort Liu, Y
collection OXFORD
description 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.
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spelling oxford-uuid:8e4d291a-13e1-49f4-aca9-e89ccc7b592e2022-03-26T22:56:46ZA crowdsourcing based mobile image translation and knowledge sharing serviceConference itemhttp://purl.org/coar/resource_type/c_5794uuid:8e4d291a-13e1-49f4-aca9-e89ccc7b592eSymplectic Elements at OxfordAssociation for Computing Machinery2010Liu, YLehdonvirta, VKleppe, MAlexandrova, TKimura, HNakajima, TTravelers 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.
spellingShingle Liu, Y
Lehdonvirta, V
Kleppe, M
Alexandrova, T
Kimura, H
Nakajima, T
A crowdsourcing based mobile image translation and knowledge sharing service
title A crowdsourcing based mobile image translation and knowledge sharing service
title_full A crowdsourcing based mobile image translation and knowledge sharing service
title_fullStr A crowdsourcing based mobile image translation and knowledge sharing service
title_full_unstemmed A crowdsourcing based mobile image translation and knowledge sharing service
title_short A crowdsourcing based mobile image translation and knowledge sharing service
title_sort crowdsourcing based mobile image translation and knowledge sharing service
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