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.
REF exploits bilingual information to create a probabilistic capitalization model using Conditional Random Fields.
Capitalizing Machine Translation
Human Language Technology Conference And Meeting Of The North American Association For Computational Linguistics
Computer Science