يمكن للقدرة على اكتشاف الإجهاد البشري تلقائيا أن تفيد العوامل الذكية الاصطناعية المشاركة في الحوسبة العاطفية والتفاعل البشري والحاسوب.الإجهاد والعاطفة كلا من الدول العاطفية البشرية، وقد أثبت الإجهاد أن يكون لها آثار مهمة على تنظيم العاطفة والتعبير عنها.على الرغم من أن سلسلة من الأساليب قد تم تأسيسها للكشف عن الإجهاد المتعدد الوسائط، فقد تم اتخاذ خطوات محدودة لاستكشاف الاعتماد الوارد في الاتجاهات الأساسية بين الإجهاد والعاطفة.في هذا العمل، نحقق في قيمة التعرف على العاطفة كملقمة مساعدة لتحسين اكتشاف الإجهاد.نقترح Muser - وهي عبارة عن بنية نموذجية قائمة على المحولات وخوارزمية تعليمية متعددة المهام الجديدة مع استراتيجية أخذ العينات الديناميكية المستندة إلى السرعة.يوضح التقييم في مجموعة بيانات المشاعر المشددة متعددة الوسائط (MUSE) أن طرازنا فعال للكشف عن الإجهاد بالمهام المساعدة الداخلية والخارجية، وتحقق نتائج أحدث النتائج.
The capability to automatically detect human stress can benefit artificial intelligent agents involved in affective computing and human-computer interaction. Stress and emotion are both human affective states, and stress has proven to have important implications on the regulation and expression of emotion. Although a series of methods have been established for multimodal stress detection, limited steps have been taken to explore the underlying inter-dependence between stress and emotion. In this work, we investigate the value of emotion recognition as an auxiliary task to improve stress detection. We propose MUSER -- a transformer-based model architecture and a novel multi-task learning algorithm with speed-based dynamic sampling strategy. Evaluation on the Multimodal Stressed Emotion (MuSE) dataset shows that our model is effective for stress detection with both internal and external auxiliary tasks, and achieves state-of-the-art results.
References used
https://aclanthology.org/
We describe our systems of subtask1 and subtask3 for SemEval-2021 Task 6 on Detection of Persuasion Techniques in Texts and Images. The purpose of subtask1 is to identify propaganda techniques given textual content, and the goal of subtask3 is to det
The problem of detecting psychological stress in online posts, and more broadly, of detecting people in distress or in need of help, is a sensitive application for which the ability to interpret models is vital. Here, we present work exploring the us
Due to the popularity of intelligent dialogue assistant services, speech emotion recognition has become more and more important. In the communication between humans and machines, emotion recognition and emotion analysis can enhance the interaction be
Existing works in multimodal affective computing tasks, such as emotion recognition and personality recognition, generally adopt a two-phase pipeline by first extracting feature representations for each single modality with hand crafted algorithms, a
Several recent studies on dyadic human-human interactions have been done on conversations without specific business objectives. However, many companies might benefit from studies dedicated to more precise environments such as after sales services or