The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …

$ k $ NN-MT is a straightforward yet powerful approach for fast domain adaptation, which
directly plugs pre-trained neural machine translation (NMT) models with domain-specific …

Automated Program Repair (APR) is defined as the process of fixing a bug/defect in the
source code, by an automated tool. APR tools have recently experienced promising results …

Machine translation (MT) has benefited from using synthetic training data originating from
translating monolingual corpora, a technique known as backtranslation. Combining …

The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …

Many language pairs are low resource, meaning the amount and/or quality of available
parallel data is not sufficient to train a neural machine translation (NMT) model which can …

In machine-learning applications, data selection is of crucial importance if good runtime
performance is to be achieved. In a scenario where the test set is accessible when the …

A pathological voice detection system is designed to detect pathological characteristics of
vocal cords from speech. Such systems are particularly susceptible to domain mismatch …

In this work, we study different ways of improving Machine Translation models by using the
subset of training data that is the most relevant to the test set. This is achieved by using …

Software testing is an important part of the software development cycle. It helps prevent
future potential defects in the system and reduce maintenance cost. However, it is often …