Bitext

We propose a novel reordering model for phrase-based statistical machine transla- tion (SMT) that uses a maximum entropy (MaxEnt) model to predicate reorderings of neighbor blocks (phrase pairs). The model …...

We present a method to transliterate names in the framework of end-to-end statistical machine translation. The system is trained to learn when to transliterate. For Arabic to English MT, we …...

This paper proposes an unsupervised word segmentation algorithm that identi- fies word boundaries in continuous source language text in order to improve the translation quality of statistical machine translation (SMT) …...

We show that jointly performing semantic role labeling (SRL) on bitext can improve SRL results on both sides. In our approach, we use monolingual SRL systems to produce ar- gument …...

We describe a novel method that extracts paraphrases from a bitext, for both the source and target languages. In order to reduce the search space, we decom- pose the phrase-table …...

We estimate the parameters of a phrase- based statistical machine translation sys- tem from monolingual corpora instead of a bilingual parallel corpus. We extend exist- ing research on bilingual lexicon …...

AbstractWe consider the construction of part-of-speech taggers for resource-poor languages. Recently, manually constructed tag dictionaries from Wiktionary and dictionaries projected via bitext have been used as type constraints to overcome …...

This work is, to our knowledge, a first attempt at a machine learning approach to cross-lingual coreference resolution, i.e. coreference resolution (CR) performed on a bitext. Focusing on CR of …...

AbstractWe consider a multilingual weakly supervised learning scenario where knowledge from annotated corpora in a resource-rich language is transferred via bitext to guide the learning in other languages. Past approaches …...

AbstractHere we present Guampa, a new software package for online collaborative translation. This system grows out of our discussions with Guarani-language activists and educators in Paraguay, and attempts to address …...

We present a new version of Phrasal, an open-source toolkit for statistical phrase- based machine translation. This revision includes features that support emerging re- search trends such as (a) tuning …...

Morphologically rich languages often lack the annotated linguistic resources required to develop accurate natural language pro- cessing tools. We propose models suitable for training morphological taggers with rich tagsets for …...

We train a neural machine translation (NMT) system to both translate source- language text and copy target-language text, thereby exploiting monolingual cor- pora in the target language. Specifically, we create …...

AbstractTraditional active learning (AL) methods for machine translation (MT) rely on heuristics. However, these heuristics are limited when the characteristics of the MT problem change due to e.g. the language …...

AbstractWe propose a framework for computer-assisted text editing. It applies to translation post-editing and to paraphrasing. Our proposal relies on very simple interactions: a human editor modifies a sentence by …...

AbstractSynthetic translations have been used for a wide range of NLP tasks primarily as a means of data augmentation. This work explores, instead, how synthetic translations can be used to …...

AbstractPretrained multilingual sequence-to-sequence models have been successful in improving translation performance for mid- and lower-resourced languages. However, it is unclear if these models are helpful in the domain adaptation setting, …...