A Machine-Learning Approach to Estimating the Referential Properties of Japanese Noun Phrases
CICLing '01 Proceedings of the Second International Conference on Computational Linguistics and Intelligent Text Processing
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
ANLC '92 Proceedings of the third conference on Applied natural language processing
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Anaphora resolution of Japanese zero pronouns with deictic reference
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Using sentence connectors for evaluating MT output
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Coreference-oriented interlingual slot structure & machine translation
CorefApp '99 Proceedings of the Workshop on Coreference and its Applications
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Fluency, adequacy, or HTER?: exploring different human judgments with a tunable MT metric
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Document-level automatic MT evaluation based on discourse representations
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Cache-based document-level statistical machine translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Extraction of salient textual patterns: synergy between lexical cohesion and contextual coherence
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Modeling lexical cohesion for document-level machine translation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper proposes the utilization of lexical cohesion to facilitate evaluation of machine translation at the document level. As a linguistic means to achieve text coherence, lexical cohesion ties sentences together into a meaningfully interwoven structure through words with the same or related meaning. A comparison between machine and human translation is conducted to illustrate one of their critical distinctions that human translators tend to use more cohesion devices than machine. Various ways to apply this feature to evaluate machine-translated documents are presented, including one without reliance on reference translation. Experimental results show that incorporating this feature into sentence-level evaluation metrics can enhance their correlation with human judgements.