A statistical approach to machine translation
Computational Linguistics
Target-Text Mediated Interactive Machine Translation
Machine Translation
Word completion: a first step toward target-text mediated IMT
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
TransType: a computer-aided translation typing system
NAACL-ANLP-EMTS '00 Proceedings of the 2000 NAACL-ANLP Workshop on Embedded machine translation systems - Volume 5
User-friendly text prediction for translators
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Generation of word graphs in statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
High quality word graphs using forward-backward pruning
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Learning finite-state models for machine translation
Machine Learning
TransType2: an innovative computer-assisted translation system
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Integration of speech to computer-assisted translation using finite-state automata
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Statistical phrase-based models for interactive computer-assisted translation
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Searching large indexes on tiny devices: optimizing binary search with character pinning
Proceedings of the 14th international conference on Intelligent user interfaces
Statistical approaches to computer-assisted translation
Computational Linguistics
HotSpots: visualizing edits to a text
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improving interactive machine translation via mouse actions
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Word graphs for statistical machine translation
ParaText '05 Proceedings of the ACL Workshop on Building and Using Parallel Texts
Exploring the effects of language skills on multilingual web search
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Incremental decoding for phrase-based statistical machine translation
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Online learning via dynamic reranking for computer assisted translation
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Cost-sensitive active learning for computer-assisted translation
Pattern Recognition Letters
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The goal of interactive machine translation is to improve the productivity of human translators. An interactive machine translation system operates as follows: the automatic system proposes a translation. Now, the human user has two options: to accept the suggestion or to correct it. During the post-editing process, the human user is assisted by the interactive system in the following way: the system suggests an extension of the current translation prefix. Then, the user either accepts this extension (completely or partially) or ignores it. The two most important factors of such an interactive system are the quality of the proposed extensions and the response time. Here, we will use a fully fledged translation system to ensure the quality of the proposed extensions. To achieve fast response times, we will use word hypotheses graphs as an efficient search space representation. We will show results of our approach on the Verbmobil task and on the Canadian Hansards task.