In the last few years, a large number of automatic evaluation metrics have been proposed for
evaluating Natural Language Generation (NLG) systems. The rapid development and …

In this review, we describe the application of one of the most popular deep learning-based
language models-BERT. The paper describes the mechanism of operation of this model, the …

We propose BERTScore, an automatic evaluation metric for text generation. Analogously to
common metrics, BERTScore computes a similarity score for each token in the candidate …

Natural language processing (NLP) has recently gained much attention for representing and
analyzing human language computationally. It has spread its applications in various fields …

Nowadays, in the globalised context in which we find ourselves, language barriers can still
be an obstacle to accessing information. On occasions, it is impossible to satisfy the demand …

Within the field of Statistical Machine Translation (SMT), the neural approach (NMT) has
recently emerged as the first technology able to challenge the long-standing dominance of …

Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …

This paper presents the results of the WMT14 shared tasks, which included a standard news
translation task, a separate medical translation task, a task for run-time estimation of …

Often, the training procedure for statistical machine translation models is based on maximum
likelihood or related criteria. A general problem of this approach is that there is only a loose …

Abstract Machine Translation (MT) is being deployed for a range of use-cases by millions of
people on a daily basis. There should, therefore, be no doubt as to the utility of MT …