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Register a new userMeasuring Translationese across Levels of Expertise: Are Professionals more Surprising than Students?
قياس الترجمة عبر مستويات الخبرة: هي المهنيين أكثر إثارة للدهشة من الطلاب؟
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تتناول الورقة الحالية تحليلا حسابيا للترجمات المهنية والطلاب الترجمات الإنجليزية إلى الألمانية التي تنتمي إلى سجلات مختلفة. بناء على النهج النظري للمعلومات، نقوم باختبار مطابقة الترجمة إلى المصدر واللغة المستهدفة من حيث حيرة نموذج اللغة العصبية على جزء من تسلسل الكلام (نقاط البيع). ينصب تركيزنا الأساسي على تنويع التسجيل مقابل التقارب، ينعكس في استخدام الإنشاءات التي تنظر إلى درجة أعلى مقابل درجة حيرة أقل. تظهر نتائجنا أنه ضد توقعاتنا، تثير الترجمات المهنية درجات حيرة أعلى من نموذج لغة مستهدف من ترجمات الطلاب. يظهر تحليل لتوزيع أنماط نقاط البيع عبر السجلات أن هذه المفارقة الواضحة هي تأثير التنويع الأسلالي الأعلى وتسجيل الحساسية في الترجمات المهنية. نتائجنا تسهم في فهم الترجمة الإنسانية والنصية على الاختلاف في النصوص الناتجة عن مختلف المترجمين، والتي هي قيمة لدراسات الترجمة ومعالجة اللغة متعددة اللغات والترجمة الآلية.
The present paper deals with a computational analysis of translationese in professional and student English-to-German translations belonging to different registers. Building upon an information-theoretical approach, we test translation conformity to source and target language in terms of a neural language model's perplexity over Part of Speech (PoS) sequences. Our primary focus is on register diversification vs. convergence, reflected in the use of constructions eliciting a higher vs. lower perplexity score. Our results show that, against our expectations, professional translations elicit higher perplexity scores from a target language model than students' translations. An analysis of the distribution of PoS patterns across registers shows that this apparent paradox is the effect of higher stylistic diversification and register sensitivity in professional translations. Our results contribute to the understanding of human translationese and shed light on the variation in texts generated by different translators, which is valuable for translation studies, multilingual language processing, and machine translation.
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