Dec 20, 2016 · We propose an approach for adapting a NMT system to a new domain. The main idea behind domain adaptation is that the availability of large out-of-domain ...
Dec 20, 2016 · In addition, our approach is fast enough to adapt an already trained system to a new domain within few hours without the need to retrain the.
Sep 6, 2024 · The main idea behind domain adaptation is that the availability of large out-of-domain training data and a small in-domain training data. We ...
Dec 20, 2016 · This paper proposes an approach for adapting a NMT system to a new domain with the main idea behind domain adaptation that the availability ...
An analysis re- veals that DDA significantly improves the NMT model's ability to generate words more frequently seen in in-domain data, indicating that DDA is ...
Neural network training has been shown to be advantageous in many natural language processing applications, such as language modelling or machine translation.
Given an in-domain dataset and a pre-trained neural model, domain adaptation can often be achieved by continuing training the model on that dataset: 'fine- ...
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Sep 6, 2024 · In this paper, we propose two novel methods for domain adaptation for the attention-only neural machine translation (NMT) model, i.e., the ...
Ensembling out-of-domain model and continued trained model: – Markus Freitag and Yaser Al-Onaizan. 2016. Fast Domain Adaptation for Neural Machine. Translation.
Feb 17, 2022 · The topic of this blog post is domain adaptation. Translation-Memory (TM) based neural machine translation (NMT) typically consists of ...