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Register a new userInfluence of user personality on dialogue task performance: A case study using a rule-based dialogue system
تأثير شخصية المستخدم على أداء مهمة الحوار: دراسة حالة باستخدام نظام حوار يستند إلى القواعد
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قد يساعد نظام حوار موجه نحو المهام مع التكيف مع شخصية المستخدم بشكل كبير تحسين أداء مهمة الحوار. ومع ذلك، يمكن أن يكون مثل هذا نظام الحوار صعبة عمليا للتنفيذ، لأنه من غير الواضح كيف تؤثر شخصية المستخدم على أداء مهمة الحوار. لاستكشاف العلاقة بين شخصية المستخدم وأداء مهمة الحوار، سجلنا المشاركين عبر الجماعة الجماعية للإجابة الأولى على استبيانات الشخصية المحددة ثم الدردشة مع نظام حوار لإنجاز المهام المعينة. تم استخدام نظام حوار يستند إلى القواعد في مهمة Wizard-of-of-of-of-of-of-of-of-of-of-ofoz (Multioz) السائدة. تم جمع وتحليل وتحليل وتحليل وتحليلها ما مجموعه 211 شخصي مشاركين وحوارات 633. كشفت النتائج أن الأشخاص المؤنسين والمنفتحين يميلون إلى فشل المهمة، في حين أن الناس العصبي كانوا أكثر عرضة للنجاح. استخرجنا الميزات المتعلقة بسلوكيات حوار المستخدم وأداء تحليل آخر لتحديد أي نوع من السلوك يؤثر على أداء المهام. ونتيجة لذلك، حددنا أن متوسط طول الكلام والانفجارات لكل كلام هي الملامح الرئيسية لسلوك الحوار مرتبطة بشدة مع كل من أداء المهام وشخصية المستخدم.
Endowing a task-oriented dialogue system with adaptiveness to user personality can greatly help improve the performance of a dialogue task. However, such a dialogue system can be practically challenging to implement, because it is unclear how user personality influences dialogue task performance. To explore the relationship between user personality and dialogue task performance, we enrolled participants via crowdsourcing to first answer specified personality questionnaires and then chat with a dialogue system to accomplish assigned tasks. A rule-based dialogue system on the prevalent Multi-Domain Wizard-of-Oz (MultiWOZ) task was used. A total of 211 participants' personalities and their 633 dialogues were collected and analyzed. The results revealed that sociable and extroverted people tended to fail the task, whereas neurotic people were more likely to succeed. We extracted features related to user dialogue behaviors and performed further analysis to determine which kind of behavior influences task performance. As a result, we identified that average utterance length and slots per utterance are the key features of dialogue behavior that are highly correlated with both task performance and user personality.
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