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Register a new userIncremental temporal summarization in multi-party meetings
تلخيص الزمني تدريجي في اجتماعات متعددة الأحزاب
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في هذا العمل، نقوم بتطوير مجموعة بيانات للتلخيص الزمني الإضافي في حوار متعدد الأحزاب.نحن نستخدم نموذجا من الحشد المصدر بموجب نهج نموذج في الحلقة لجمع الملخصات ومقارنة البيانات مع ملخصات الخبراء.نحن نستفيد نموذج جيل السؤال لإنشاء أسئلة تلقائيا من الحوار، والذي يمكن استخدامه للتحقق من صحة مشاركة المستخدمين وربما لفت انتباه المستخدم أيضا إلى المحتويات ثم تحتاج إلى تلخيص.نقوم بعد ذلك بتطوير العديد من النماذج لتوليد موجز موجز في السيناريو الزمني الإضافي.نقوم بإجراء تحليل مفصل للنتائج وإظهار أنه بما في ذلك السياق الماضي في الجيل الموجز غلة ملخصات أفضل.
In this work, we develop a dataset for incremental temporal summarization in a multiparty dialogue. We use crowd-sourcing paradigm with a model-in-loop approach for collecting the summaries and compare the data with the expert summaries. We leverage the question generation paradigm to automatically generate questions from the dialogue, which can be used to validate the user participation and potentially also draw attention of the user towards the contents then need to summarize. We then develop several models for abstractive summary generation in the Incremental temporal scenario. We perform a detailed analysis of the results and show that including the past context into the summary generation yields better summaries.
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