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Register a new userDoes It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework
هل التقاط ستيل؟إطار تقييم النمط اللغوي المعياري والمقر الرئيسي
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النمط هو جزء لا يتجزأ من اللغة الطبيعية.ومع ذلك، فإن أساليب التقييم لتدابير النمط نادرة، وغالبا ما تكون المهام الخاصة وعادة ما لا تتحكم في المحتوى.نقترح إطار تقييم النمط المعياري والحبوب المحتوى ومقره المحتوى (STEL) لاختبار أداء أي نموذج يمكن مقارنة جملتين على النمط.نحن نوضح ستيل مع أبعاد عامين من النمط (رسمي / غير رسمي وبسيط / معقد) بالإضافة إلى خصائصين محددة للأسلوب (Contrac'tion and Numb3r البديلة).نجد أن الأساليب القائمة على BERT تفوق إصدارات بسيطة من تدابير النمط الشائعة الاستخدام مثل 3 غرامات وترقيب الترقيم والنهج القائمة على LIWC.نحن ندعو إضافة مهام أخرى وثيمات مهمة إلى ستيل ونأمل في تسهيل تحسين التدابير الحساسة للنمط.
Style is an integral part of natural language. However, evaluation methods for style measures are rare, often task-specific and usually do not control for content. We propose the modular, fine-grained and content-controlled similarity-based STyle EvaLuation framework (STEL) to test the performance of any model that can compare two sentences on style. We illustrate STEL with two general dimensions of style (formal/informal and simple/complex) as well as two specific characteristics of style (contrac'tion and numb3r substitution). We find that BERT-based methods outperform simple versions of commonly used style measures like 3-grams, punctuation frequency and LIWC-based approaches. We invite the addition of further tasks and task instances to STEL and hope to facilitate the improvement of style-sensitive measures.
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