A maximum entropy approach to natural language processing
Computational Linguistics
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
On-Line Handwriting Recognition System for Tamil Handwritten Characters
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Statistical approaches to computer-assisted translation
Computational Linguistics
Multimodal interactive transcription of text images
Pattern Recognition
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
On multimodal interactive machine translation using speech recognition
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Improving on-line handwritten recognition in interactive machine translation
Pattern Recognition
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Interactive machine translation (IMT) [1] is an alternative approach to machine translation, integrating human expertise into the automatic translation process. In this framework, a human iteratively interacts with a system until the output desired by the human is completely generated. Traditionally, interaction has been performed using a keyboard and a mouse. However, the use of touchscreens has been popularised recently. Many touchscreen devices already exist in the market, namely mobile phones, laptops and tablet computers like the iPad. In this work, we propose a new interaction modality to take advantage of such devices, for which online handwritten text seems a very natural way of input. Multimodality is formulated as an extension to the traditional IMT protocol where the user can amend errors by writing text with an electronic pen or a stylus on a touchscreen. Different approaches to modality fusion have been studied. In addition, these approaches have been assessed on the Xerox task. Finally, a thorough study of the errors committed by the online handwritten system will show future work directions.