Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A knowledge-free method for capitalized word disambiguation
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Discriminative language modeling with conditional random fields and the perceptron algorithm
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Temporal Issues and Recognition Errors on the Capitalization of Speech Transcriptions
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Language dynamics and capitalization using maximum entropy
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Formatting time-aligned ASR transcripts for readability
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Statistical machine translation enhancements through linguistic levels: A survey
ACM Computing Surveys (CSUR)
| Hi-index | 0.00 |
We present a probabilistic bilingual capitalization model for capitalizing machine translation outputs using conditional random fields. Experiments carried out on three language pairs and a variety of experiment conditions show that our model significantly outperforms a strong monolingual capitalization model baseline, especially when working with small datasets and/or European language pairs.