The boundaries of meaning: a case study in neural machine translation

Balashov, Yuri

doi:10.1080/0020174x.2022.2113429

Cited by 3 publications

(1 citation statement)

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“…Out of which, the authors developed one phrase-based SMT system and one NMT system using byte-pair embedding for the HI↔MR pair. In [51], authors used a Transformer-based NMT with sentencepiece for subword embedding on HI↔MR language pair [61]. In [52], authors used the Transformer-NMT for multilingual model training and evaluated the result on the HI↔MR pair.…”

Section: Related Workmentioning

confidence: 99%

Study of Local Site Conditions for Seismic Hazard Assessment at the BHU Campus, Varanasi, North India, using Ambient Noise Measurements

Kumari

Singh

Shankar

et al. 2022

Journal of the Geological Society of India

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The use of subword embedding has proved to be a major innovation in Neural Machine Translation (NMT). It helps NMT to learn better context vectors for Low Resource Languages (LRLs) so as to predict the target words by better modelling the morphologies of the two languages and also the morphosyntax transfer. Even so, their performance for translation in Indian language to Indian language scenario is still not as good as for resource-rich languages. One reason for this is the relative morphological richness of Indian languages, while another is that most of them fall into the extremely low resource or zero-shot categories. Since most major Indian languages use Indic or Brahmi origin scripts, the text written in them is highly phonetic in nature and phonetically similar in terms of abstract letters and their arrangements. We use these characteristics of Indian languages and their scripts to propose an approach based on common multilingual Latin-based encodings (WX notation) that take advantage of language similarity while addressing the morphological complexity issue in NMT. These multilingual Latin-based encodings in NMT, together with Byte Pair Embedding (BPE) allow us to better exploit their phonetic and orthographic as well as lexical similarities to improve the translation quality by projecting different but similar languages on the same orthographic-phonetic character space. We verify the proposed approach by demonstrating experiments on similar language pairs (Gujarati↔Hindi, Marathi↔Hindi, Nepali↔Hindi, Maithili↔Hindi, Punjabi↔Hindi, and Urdu↔Hindi) under low resource conditions. The proposed approach shows an improvement in a majority of cases, in one case as much as ∼10 BLEU points compared to baseline techniques for similar language pairs. We also get up to ∼1 BLEU points improvement on distant and zero-shot language pairs.

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Section: Related Workmentioning

confidence: 99%

Study of Local Site Conditions for Seismic Hazard Assessment at the BHU Campus, Varanasi, North India, using Ambient Noise Measurements

Kumari

Singh

Shankar

et al. 2022

Journal of the Geological Society of India

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Machine translation by projecting text into the same phonetic-orthographic space using a common encoding

Kumar,

Parida,

Pratap

et al. 2023

Sādhanā

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Effects of pre-editing operations on audiovisual translation using TRADOS: an experimental analysis of Saudi students’ translations

Bounaas,

Zemni,

Al Shehri

et al. 2023

Texto livre

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Neural Machine Translation (NMT) is a revolutionary innovation that has had a significant impact not only on the translation industry but also on translation studies. This technology is creating new opportunities for shaping identities and generating new knowledge and perspectives. This led researchers to undeniably and increasingly conduct studies to improve NMT performance. These studies involve assessing the quality of the output, determining the extent to which humans can be involved in the machine-based process, and proposing solutions to redress the deficiencies. In this regard, the paper focuses on the impact of pre-editing (PE) operations on the translation of audiovisual children’s literary texts (subtitles) from English to Arabic using TRADOS. The work seeks to accomplish a number of pre-editing-related research goals in the context of Arabic NMT systems. Initially, it aims to define and clarify the idea of PE and its function in enhancing Arabic NMT systems’ performance. Second, it looks at PE mechanisms and methods and how they might improve the appropriateness and accuracy of Arabic machine translation. Additionally, the study attempts to investigate the value of PE in enhancing the Arabic translation of audiovisual children’s literature. The study also seeks to list the difficulties and restrictions related to PE and suggest viable strategies to get over them. Finally, the paper offers suggestions for further investigation into NMT systems using Arabic and PE. To achieve these goals, the researchers conducted a human evaluation of NMT for two animated movie subtitles and determined the necessary PE operations. The findings revealed that PE has the potential to improve the quality of literary translations and enhance their comprehensibility and acceptability.

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The boundaries of meaning: a case study in neural machine translation

Cited by 3 publications

References 50 publications

Study of Local Site Conditions for Seismic Hazard Assessment at the BHU Campus, Varanasi, North India, using Ambient Noise Measurements

Study of Local Site Conditions for Seismic Hazard Assessment at the BHU Campus, Varanasi, North India, using Ambient Noise Measurements

Machine translation by projecting text into the same phonetic-orthographic space using a common encoding

Effects of pre-editing operations on audiovisual translation using TRADOS: an experimental analysis of Saudi students’ translations

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