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Register a new userWould you like to tell me more? Generating a corpus of psychotherapy dialogues
هل ترغب في أن تخبرني أكثر؟توليد جثة حوارات العلاج النفسي
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إن اكتساب كوربوس للحوار هو خطوة أساسية في عملية تدريب نموذج الحوار. في هذا السياق، تم تصميم عمليات الاستحواذ من Corpora إما لمهام استرجاع المعلومات أو ملء الفتحات المفتوحة (E.G. Restaurant). ومع ذلك، كان هناك بحث نادر في مشكلة جمع المحادثات الشخصية مع المستخدمين على مدى فترة طويلة من الزمن. في هذه الورقة نركز على أنواع الحوارات المطلوبة لتطبيقات الصحة العقلية. أحد هذه الأنواع هو حوار المتابعة الذي سيبدأ فيه مواد عملية نفسية في مراجعة التقدم المحرز في تدخل العلاج السلوكي المعرفي (CBT). يتم تحقيق تنازلات الحوارات من خلال المحفزات النصية المقدمة لكتاب الحوار. نقترح خوارزمية أوتوماتيكية تنشئ محفزات نصية من الروايات الشخصية التي تم جمعها أثناء تدخلات العلاج النفسي. يتم تقديم المحفزات التي تم إنشاؤها تلقائيا كصحة للكتاب الحوار بعد المبادئ التوجيهية المبدئية. نقوم بتحليل الجودة اللغوية للجنة التي تم جمعها ومقارنة عروض أخصائيي الأطباء النفسيين وكتاب الحوار غير الخبراء. علاوة على ذلك، نبلغ عن التقييم البشري لنموذج اختيار الاستجابة القائمة على Corpus.
The acquisition of a dialogue corpus is a key step in the process of training a dialogue model. In this context, corpora acquisitions have been designed either for open-domain information retrieval or slot-filling (e.g. restaurant booking) tasks. However, there has been scarce research in the problem of collecting personal conversations with users over a long period of time. In this paper we focus on the types of dialogues that are required for mental health applications. One of these types is the follow-up dialogue that a psychotherapist would initiate in reviewing the progress of a Cognitive Behavioral Therapy (CBT) intervention. The elicitation of the dialogues is achieved through textual stimuli presented to dialogue writers. We propose an automatic algorithm that generates textual stimuli from personal narratives collected during psychotherapy interventions. The automatically generated stimuli are presented as a seed to dialogue writers following principled guidelines. We analyze the linguistic quality of the collected corpus and compare the performances of psychotherapists and non-expert dialogue writers. Moreover, we report the human evaluation of a corpus-based response-selection model.
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