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Register a new userA Grounded Well-being Conversational Agent with Multiple Interaction Modes: Preliminary Results
وكيل محادثة محادثة متأثرة مع أوضاع متعددة التفاعل: النتائج الأولية
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تقنيات تعزيز الرفاهية والرعاية الصحية والرصد هي في ارتفاع. ومع ذلك، على الرغم من اهتمام المرضى، تعاني هذه التقنيات من اعتماد منخفض. فرضية واحدة لهذا التبني المحدود هو فقدان التفاعل البشري هو أمر أساسي لقاءات الطبيب المريض. في هذه الورقة، نسعى إلى معالجة هذا القيد من خلال وكيل محادثة يعتمد جانب واحد من تفاعلات الطبيب الواحد في شخصيا: صورة شخصية بشرية لتسهيل الإجابة على الأسئلة الطبية. هذا أقرب إلى سيناريو شخصيا حيث قد يشير الطبيب إلى جسم الإنسان أو قد يشير المريض إلى جسدهم للتعبير عن شروطهم. بالإضافة إلى ذلك، يحتوي وكيلنا على أوضاع متعددة التفاعل، قد تعطي المزيد من الخيارات للمريض لاستخدام الوكيل، وليس فقط للمسألة الطبية الإجابة، ولكن أيضا للانخراط في محادثات حول الموضوعات العامة والأحداث الحالية. كل من الصورة الرمزية، ويمكن أن تساعد أوضاع التفاعل المتعددة في تحسين الالتزام. نقدم نظرة عامة رفيعة المستوى على تصميم وكيلنا، ماري بوت الرفاهية. نحن نبلغ أيضا عن تفاصيل التنفيذ من النموذج الأولي المبكر لدينا، وتقديم النتائج الأولية.
Technologies for enhancing well-being, healthcare vigilance and monitoring are on the rise. However, despite patient interest, such technologies suffer from low adoption. One hypothesis for this limited adoption is loss of human interaction that is central to doctor-patient encounters. In this paper we seek to address this limitation via a conversational agent that adopts one aspect of in-person doctor-patient interactions: A human avatar to facilitate medical grounded question answering. This is akin to the in-person scenario where the doctor may point to the human body or the patient may point to their own body to express their conditions. Additionally, our agent has multiple interaction modes, that may give more options for the patient to use the agent, not just for medical question answering, but also to engage in conversations about general topics and current events. Both the avatar, and the multiple interaction modes could help improve adherence. We present a high level overview of the design of our agent, Marie Bot Wellbeing. We also report implementation details of our early prototype , and present preliminary results.
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