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Register a new userTIAGE: A Benchmark for Topic-Shift Aware Dialog Modeling
TIAGE: معيارا للنمذجة في حوار الحوار Topic-Shift
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المحادثات الإنسانية تتطور بشكل طبيعي حول مواضيع مختلفة والتحرك بطلاقة بينهما.في البحوث على أنظمة الحوار، غالبا ما يتم تجاهل القدرة على الانتقال بنشاط وسلاسة إلى مواضيع جديدة.في هذه الورقة، نقدم TIAGE، وهو مؤشر مربع حوار مدرك مواضيع جديد يستخدم باستخدام التعليقات التوضيحية البشرية على نوبات الموضوع.استنادا إلى TIAGE، نقدم ثلاث مهام للتحقيق في سيناريوهات مختلفة من النمذجة التي تحول المواضيع في إعدادات الحوار: الكشف عن موضوع التحول، وموضوع تحول توليد استجابة استجابة وتوليد التدريب على الموضوع.تشير التجارب في هذه المهام إلى أن إشارات التحول في Tiage مفيدة لتوليد استجابة الموضوع.من ناحية أخرى، ما زالت أنظمة الحوار تكافح لتحديد وقت تغيير الموضوع.يشير هذا إلى أن هناك حاجة إلى مزيد من الأبحاث في نمذجة الحوار Topic-Shift Cy.
Human conversations naturally evolve around different topics and fluently move between them. In research on dialog systems, the ability to actively and smoothly transition to new topics is often ignored. In this paper we introduce TIAGE, a new topic-shift aware dialog benchmark constructed utilizing human annotations on topic shifts. Based on TIAGE, we introduce three tasks to investigate different scenarios of topic-shift modeling in dialog settings: topic-shift detection, topic-shift triggered response generation and topic-aware dialog generation. Experiments on these tasks show that the topic-shift signals in TIAGE are useful for topic-shift response generation. On the other hand, dialog systems still struggle to decide when to change topic. This indicates further research is needed in topic-shift aware dialog modeling.
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