QUES: A Quality Estimation System of Arabic to English Translation

Ali, Manar Salamah; Alatawi, Anfal; Alsahafi, Bayader; Noorwali, Najwa

doi:10.14569/ijacsa.2020.0110732

Cited by 2 publications

(2 citation statements)

References 17 publications

(19 reference statements)

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“…Performance measurements in the MT system play an indispensable role in determining the efficacy of the existing system and the requirement of optimization. Regarding MT system evaluation, human evaluation and several other matrices are available [39].…”

Section: Mt Performance Measurementmentioning

confidence: 99%

Recent Progress, Emerging Techniques, and Future Research Prospects of Bangla Machine Translation: A Systematic Review

Akhand¹,

Roy²,

Dhar³

et al. 2021

IJACSA

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Machine Translation (MT), the way of translating texts or documents from a source language to a target language automatically without human intervention, has gained popularity in the growing information technology-based era of globalization. Bangla is a major language, and several MT studies with different tools and techniques have been investigated in the last two decades. Considering the importance of the Bangla language and its prospects in MT studies, this study provides a comprehensive review of existing Bangla MT studies to meet the timely demand. Specifically, at first, the basic ideas of different MT methods (Rule-based, Example-based, Statistical, Neural, and Hybrid) and performance measures of MT are presented as a background study of the present review. Then an overview of the Bangla language and a brief description of the available Bangla-English corpora are provided. Next, a description of the existing Bangla MT studies is provided categorically following the common strategic fashion to create a valuable reference for current researchers in the field that is also suitable for nonexpert users. The achieved performances of individual methods are also compared in a tabular form. Finally, a number of future research prospects are revealed from the studies, encouraging researchers and practitioners to develop a better and comprehensive Bangla MT system.

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Section: Mt Performance Measurementmentioning

confidence: 99%

Recent Progress, Emerging Techniques, and Future Research Prospects of Bangla Machine Translation: A Systematic Review

Akhand¹,

Roy²,

Dhar³

et al. 2021

IJACSA

View full text Add to dashboard Cite

show abstract

“…However, the main motivation for using manual evaluation (adequacy and fluency criteria) to estimate the translation quality in Arabic-English language pairs in the present research has been the lack of any other studies using these methods in this context. In relation to this, Ali et al (2020) have introduced an automatic tool that does not require access to the reference translation or the source in order to assess the quality of translated content in Arabic-to-English translations. A black-box method is used to extract a feature set from the Arabic-English language pair, while a five-point scale is used to measure the adequacy and fluency.…”

Section: Manual Evaluation Developmentmentioning

confidence: 99%

Comparative Evaluation of Translation Memory (TM) and Machine Translation (MT) Systems in Translation between Arabic and English

Khaled¹

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In general, advances in translation technology tools have enhanced translation quality significantly. Unfortunately, however, it seems that this is not the case for all language pairs. A concern arises when the users of translation tools want to work between different language families such as Arabic and English. The main problems facing Arabic<>English translation tools lie in Arabic’s characteristic free word order, richness of word inflection – including orthographic ambiguity – and optionality of diacritics, in addition to a lack of data resources. The aim of this study is to compare the performance of translation memory (TM) and machine translation (MT) systems in translating between Arabic and English.The research evaluates the two systems based on specific criteria relating to needs and expected results. The first part of the thesis evaluates the performance of a set of well-known TM systems when retrieving a segment of text that includes an Arabic linguistic feature. As it is widely known that TM matching metrics are based solely on the use of edit distance string measurements, it was expected that the aforementioned issues would lead to a low match percentage. The second part of the thesis evaluates multiple MT systems that use the mainstream neural machine translation (NMT) approach to translation quality. Due to a lack of training data resources and its rich morphology, it was anticipated that Arabic features would reduce the translation quality of this corpus-based approach. The systems’ output was evaluated using both automatic evaluation metrics including BLEU and hLEPOR, and TAUS human quality ranking criteria for adequacy and fluency.The study employed a black-box testing methodology to experimentally examine the TM systems through a test suite instrument and also to translate Arabic English sentences to collect the MT systems’ output. A translation threshold was used to evaluate the fuzzy matches of TM systems, while an online survey was used to collect participants’ responses to the quality of MT system’s output. The experiments’ input of both systems was extracted from Arabic<>English corpora, which was examined by means of quantitative data analysis. The results show that, when retrieving translations, the current TM matching metrics are unable to recognise Arabic features and score them appropriately. In terms of automatic translation, MT produced good results for adequacy, especially when translating from Arabic to English, but the systems’ output appeared to need post-editing for fluency. Moreover, when retrievingfrom Arabic, it was found that short sentences were handled much better by MT than by TM. The findings may be given as recommendations to software developers.

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QUES: A Quality Estimation System of Arabic to English Translation

Cited by 2 publications

References 17 publications

Recent Progress, Emerging Techniques, and Future Research Prospects of Bangla Machine Translation: A Systematic Review

Recent Progress, Emerging Techniques, and Future Research Prospects of Bangla Machine Translation: A Systematic Review

Comparative Evaluation of Translation Memory (TM) and Machine Translation (MT) Systems in Translation between Arabic and English

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