Bilingual lexicon induction is the task of inducing word translations from monolingual
corpora in two languages. In this article we present the most comprehensive analysis of …

We develop two techniques for analyzing the effect of porting a machine translation system
to a new domain. One is a macro-level analysis that measures how domain shift affects …

In this paper, we propose a method which uses semi-supervised convolutional neural
networks (CNNs) to select in-domain training data for statistical machine translation. This …

Large-scale annotated corpora are a prerequisite to developing high-performance NLP
systems. Such corpora are expensive to produce, limited in size, often demanding linguistic …

Abstract The multilingual Paraphrase Database (PPDB) is a freely available automatically
created resource of paraphrases in multiple languages. In statistical machine translation …

Inspired by previous work, where decipherment is used to improve machine translation, we
propose a new idea to combine word alignment and decipherment into a single learning …

We introduce into Bayesian decipherment a base distribution derived from similarities of
word embeddings. We use Dirichlet multinomial regression (Mimno and McCallum, 2012) to …

Differences in domains of language use between training data and test data have often
been reported to result in performance degradation for phrase-based machine translation …

Abstract Out-of-vocabulary (OOV) word is a crucial problem in statistical machine translation
(SMT) with low resources. OOV paraphrasing that augments the translation model for the …

In previous work we showed that when using an SMT model trained on old-domain data to
translate text in a new-domain, most errors are due to unseen source words, unseen target …