Neural machine translation (NMT) is a deep learning based approach for machine
translation, which yields the state-of-the-art translation performance in scenarios where …

We introduce a new domain expert mixture (DEMix) layer that enables conditioning a
language model (LM) on the domain of the input text. A DEMix layer is a collection of expert …

(57) ABSTRACT A system and method for estimating parameters for features of a translation
scoring function for scoring candidate trans lations in a target domain are provided. Given a …

When building machine translation systems, one often needs to make the best out of
heterogeneous sets of parallel data in training, and to robustly handle inputs from …

This article reports on the results of a project that aimed to investigate the usability of raw
machine translated technical support documentation for a commercial online file storage …

Neural machine translation (NMT) has been prominent in many machine translation tasks.
However, in some domain-specific tasks, only the corpora from similar domains can improve …

Domain adaptation is an old and vexing problem for machine translation systems. The most
common and successful approach to supervised adaptation is to fine-tune a baseline system …

Neural machine translation (NMT) is a deep learning based approach for machine
translation, which outperforms traditional statistical machine translation (SMT) and yields the …

While domain adaptation techniques for SMT have proven to be effective at improving
translation quality, their practicality for a multi-domain environment is often limited because …

In this paper, we tackle the problem of domain adaptation of statistical machine translation
(SMT) by exploiting domain-specific data acquired by domain-focused crawling of text from …