Error classification and analysis for machine translation quality assessment

M Popović - Translation quality assessment: From principles to …, 2018 - Springer
This chapter presents an overview of different approaches and tasks related to classification
and analysis of errors in machine translation (MT) output. Manual error classification is a …

[PDF][PDF] WordNet gloss translation for under-resourced languages using multilingual neural machine translation

BR Chakravarthi, M Arcan… - Proceedings of the second …, 2019 - aclanthology.org
In this paper, we translate the glosses in the English WordNet based on the expand
approach for improving and generating wordnets with the help of multilingual neural …

Comparison of different orthographies for machine translation of under-resourced dravidian languages

BR Chakravarthi, M Arcan… - 2nd Conference on …, 2019 - drops.dagstuhl.de
Under-resourced languages are a significant challenge for statistical approaches to
machine translation, and recently it has been shown that the usage of training data from …

A data augmentation method for English-Vietnamese neural machine translation

NL Pham, TV Pham - IEEE Access, 2023 - ieeexplore.ieee.org
The translation quality of machine translation systems depends on the parallel corpus used
for training, particularly on the quantity and quality of the corpus. However, building a high …

A reverse positional encoding multi-head attention-based neural machine translation model for arabic dialects

LH Baniata, S Kang, IKE Ampomah - Mathematics, 2022 - mdpi.com
Languages with a grammatical structure that have a free order for words, such as Arabic
dialects, are considered a challenge for neural machine translation (NMT) models because …

A survey of orthographic information in machine translation

BR Chakravarthi, P Rani, M Arcan, JP McCrae - SN computer science, 2021 - Springer
Abstract Machine translation is one of the applications of natural language processing which
has been explored in different languages. Recently researchers started paying attention …

A transformer-based neural machine translation model for Arabic dialects that utilizes subword units

LH Baniata, IKE Ampomah, S Park - Sensors, 2021 - mdpi.com
Languages that allow free word order, such as Arabic dialects, are of significant difficulty for
neural machine translation (NMT) because of many scarce words and the inefficiency of …

Multilingual neural machine translation for low-resource languages

SM Lakew, M Federico, M Negri… - IJCoL. Italian Journal …, 2018 - journals.openedition.org
In recent years, Neural Machine Translation (NMT) has been shown to be more effective
than phrase-based statistical methods, thus quickly becoming the state of the art in machine …

Neural machine translation into language varieties

SM Lakew, A Erofeeva, M Federico - arXiv preprint arXiv:1811.01064, 2018 - arxiv.org
Both research and commercial machine translation have so far neglected the importance of
properly handling the spelling, lexical and grammar divergences occurring among language …

North korean neural machine translation through south korean resources

H Kim, H Tosho, S Moon, N Okazaki… - ACM Transactions on …, 2023 - dl.acm.org
South and North Korea both use the Korean language. However, Korean natural language
processing (NLP) research has mostly focused on South Korean language. Therefore …