تحليل الخطأ في ترجمة جوجل: دراسة حالة لنص طبي
DOI:
https://doi.org/10.31185/eduj.Vol2.Iss43.2235چکیده
أدى توفير الوقت والجهود إلى ضرورة استخدام أنظمة الترجمة الآلية مثل ترجمة جوجل Google Translate لترجمة النصوص في جميع أنحاء العالم. كانت ترجمة جوجل خلال العقود الماضية محور الإهتمام لكونها أكثر أنظمة الترجمة الآلية استخدامًا وذلك لسرعتها والنتائج شبه الدقيقة التي أظهرتها. نشأت الحاجة لهذه الدراسة من حقيقة أن ترجمة الإنجليزية والعربية الآلية من خلال تطبيق جوجل يوجد فيها العديد من الأخطاء التي يجب تسليط الضوء عليها لأن كلتا اللغتين تنتمي إلى أنظمة لغوية مختلفة. من أجل تقييم جودة ترجمة جوجل، استخدم هذ البحث تحليل الخطأ بهدف تحديد أنواع الأخطاء المختلفة في ترجمة جوجل. ركز هذا التحليل على دراسة عدم تطابق المكونات النحوية والصرفية و المعجمية و الدلالية التي وجدت في النص المصدر و الهدف. دراسة الحالة لهذا البحث هي نص طبي إنجليزي تم اختياره لتقييم دقة وفائدة ترجمة جوجل في ترجمة العبارات و المصطلحات الطبية الإنجليزية. أظهرت النتائج أن الأخطاء الأكثر تكرارا كانت أخطاءا دلالية و نحوية بنسبة (30٪) لكل خطأ بينما حلت الأخطاء المورفولوجية على المرتبة الثانية بنسبة (25%) أما الأخطاء المعجمية فقد حلت في المرتبة الأخيرة بنسبة (15%).
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t is shown that lexical and semantic errors have
most impact on sentence level ranking. Furthermore, highly ranked sentences clearly
exhibit low number of grammatical errors, however the relation between grammat-
ical errors and poorly ranked segments remained unclear. Apart from this, high
inter-annotator agreement between two annotators is reported, which contradicts
the results from former studies. The most probable factor is removing words with
position disagreement from calculation which increased the agreement between the
error types
is shown that lexical and semantic errors have
most impact on sentence level ranking. Furthermore, highly ranked sentences clearly
exhibit low number of grammatical errors, however the relation between grammat-
ical errors and poorly ranked segments remained unclear. Apart from this, high
inter-annotator agreement between two annotators is reported, which contradicts
the results from former studies. The most probable factor is removing words with
position disagreement from calculation which increased the agreement between the
errrgest correlation is observed for lexical errors and missing words.
Additional very interesting finding is that the human perception of quality does not
necessarily depend on frequency of the given error type – a sentence with a low
overall score can easily contain less missing words and/or lexical errors than an-
other sentence with
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حق نشر 2021 Journal of Education College Wasit University

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