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Register a new userThink Before You Speak: Learning to Generate Implicit Knowledge for Response Generation by Self-Talk
فكر قبل أن تتحدث: تعلم توليد معرفة ضمنية لجيل الاستجابة عن طريق الحديث الذاتي
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يقدم البشر ردود مناسبة لا يستند فقط إلى كلام الحوار السابق ولكن أيضا على المعرفة الخلفية الضمنية مثل الحس السليم. على الرغم من أن نماذج توليد الاستجابة العصبية تنتج ردود تشبه الإنسان، إلا أنها في الغالب من طرفا ولا تولد أسباب وسيطة بين تاريخ الحوار والردود. يهدف هذا العمل إلى الدراسة إذا وكيف يمكننا تدريب نموذج RG الذي يتحدث عن نفسه لتوليد معرفة ضمنية قبل تقديم ردود. نحن نحقق مزيد من التحقيق في هذه النماذج عندما تولد معرفة خلفية ضمنية وعندما لا يكون ذلك ضروريا. تظهر النتائج التجريبية مقارنة بالنماذج التي تولد الردود مباشرة بالنظر إلى تاريخ الحوار، وتنتج نماذج الحديث الذاتي استجابات أفضل بجودة وفقا للتقييم البشري على الحكم النحوي والتماسك والعمل. والنماذج التي يتم تدريبها على تحديد متى يتحدث التحدث الذاتي إلى تحسين جودة الاستجابة. تبين تحليل المعرفة الضمنية الناتجة أن الطرز تستخدم معظمها المعرفة بشكل مناسب في الردود.
Humans make appropriate responses not only based on previous dialogue utterances but also on implicit background knowledge such as common sense. Although neural response generation models seem to produce human-like responses, they are mostly end-to-end and not generating intermediate grounds between a dialogue history and responses. This work aims to study if and how we can train an RG model that talks with itself to generate implicit knowledge before making responses. We further investigate can such models identify when to generate implicit background knowledge and when it is not necessary. Experimental results show that compared with models that directly generate responses given a dialogue history, self-talk models produce better-quality responses according to human evaluation on grammaticality, coherence, and engagingness. And models that are trained to identify when to self-talk further improves the response quality. Analysis on generated implicit knowledge shows that models mostly use the knowledge appropriately in the responses.
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