Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer by Machine Translation Systems

Saadany, Hadeel; Orăsan, Constantin; Mohamed, Emad; Tantawy, Ashraf

doi:10.26615/978-954-452-072-4_137

Cited by 1 publication

(1 citation statement)

References 18 publications

(12 reference statements)

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“…Evaluative studies stressed the significance of translation evaluation to improve the performance of Arabic MT engines and suggest strategies to overcome relevant shortcomings [55,61,65]. Considering the limited research on Arabic MT effectiveness in dealing with specialized content [100], some studies addressed MT shortcomings in translating specialized texts or textual components such as the legal discourse [100], literary features [66], proverbs [67], sentiment words [101], relative clauses [57], as well as social media vernacular [102]. Evaluative studies continued to dominate the literature on MT systems to highlight their affordances and limitations in terms of adequacy, accuracy, fluency, context sensitivity, terminology and other criteria and called for complementarity between MT and HT via pre-editing and postediting [50,53,58,63,70,103].…”

Section: Between 2020-2023mentioning

confidence: 99%

Systematic Review of English/Arabic Machine Translation Postediting: Implications for AI Application in Translation Research and Pedagogy

Omar,

Salih

2024

Informatics

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The twenty-first century has witnessed an extensive evolution in translation practice thanks to the accelerated progress in machine translation tools and software. With the increased scalability and availability of machine translation software empowered by artificial intelligence, translation students and practitioners have continued to show an unwavering reliance on automatic translation systems. Academically, there is little recognition of the need to develop machine translation skillsets amongst translation learners in English/Arabic translation programs. This study provides a systematic review of machine translation postediting with reference to English/Arabic machine translation. Using the Preferred Reporting Items for Systematic Review and Meta-Analysis, the paper reviewed 60 studies conducted since the beginning of the twenty-first century and classified them by different metrics to identify relevant trends and research gaps. The results showed that research on the topic has been primarily prescriptive, concentrating on evaluating and developing machine translation software while neglecting aspects related to translators’ skillsets and competencies. The paper highlights the significance of postediting as an important digital literacy to be developed among Arabic translation students and the need to bridge the existing research and pedagogic gap in MT education.

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