Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Word sense disambiguation with pictures
HLT-NAACL-LWM '04 Proceedings of the HLT-NAACL 2003 workshop on Learning word meaning from non-linguistic data - Volume 6
Shift: a technique for operating pen-based interfaces using touch
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Text Entry Systems: Mobility, Accessibility, Universality
Text Entry Systems: Mobility, Accessibility, Universality
How well do visual verbs work in daily communication for young and old adults?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Toward communicating simple sentences using pictorial representations
Machine Translation
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Multilingual mobile-phone translation services for world travelers
COLING '08 22nd International Conference on on Computational Linguistics: Demonstration Papers
A text-to-picture synthesis system for augmenting communication
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
On the importance of pivot language selection for statistical machine translation
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Rush: repeated recommendations on mobile devices
Proceedings of the 15th international conference on Intelligent user interfaces
Translation by iterative collaboration between monolingual users
Proceedings of Graphics Interface 2010
picoTrans: an icon-driven user interface for machine translation on mobile devices
Proceedings of the 16th international conference on Intelligent user interfaces
picoTrans: using pictures as input for machine translation on mobile devices
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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picoTrans is a prototype system that introduces a novel icon-based paradigm for cross-lingual communication on mobile devices. Our approach marries a machine translation system with the popular picture book. Users interact with picoTrans by pointing at pictures as if it were a picture book; the system generates natural language from these icons and the user is able to interact with the icon sequence to refine the meaning of the words that are generated. When users are satisfied that the sentence generated represents what they wish to express, they tap a translate button and picoTrans displays the translation. Structuring the process of communication in this way has many advantages. First, tapping icons is a very natural method of user input on mobile devices; typing is cumbersome and speech input errorful. Second, the sequence of icons which is annotated both with pictures and bilingually with words is meaningful to both users, and it opens up a second channel of communication between them that conveys the gist of what is being expressed. We performed a number of evaluations of picoTrans to determine: its coverage of a corpus of in-domain sentences; the input efficiency in terms of the number of key presses required relative to text entry; and users' overall impressions of using the system compared to using a picture book. Our results show that we are able to cover 74% of the expressions in our test corpus using a 2000-icon set; we believe that this icon set size is realistic for a mobile device. We also found that picoTrans requires fewer key presses than typing the input and that the system is able to predict the correct, intended natural language sentence from the icon sequence most of the time, making user interaction with the icon sequence often unnecessary. In the user evaluation, we found that in general users prefer using picoTrans and are able to communicate more rapidly and expressively. Furthermore, users had more confidence that they were able to communicate effectively using picoTrans.