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Empathetic Textual Speech of Conversational Agents in Client-Centered Therapy

Allahverdiyeva, Aydan (2021) Empathetic Textual Speech of Conversational Agents in Client-Centered Therapy.

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Abstract:Despite society becoming more aware of mental health and the importance of therapy, it still may be hard for people to undergo therapy for various reasons: the therapy sessions may not be available, they can be expensive, time-consuming or the person may not be emotionally ready to face the therapy sessions. Conversational agents (CAs) may play the role of therapist, thus making the therapy more accessible. However, the current limitations of the textual speech of the agents do not allow one to open up and talk honestly about the problems as one would in real therapy. This research analyzed empathy factors of the textual speech and their influence on the engagement of the patients with therapy and investigated how to make the textual speech of the conversational agents more empathetic for therapy. Due to the low scope and a low number of participants, the research could not provide any certain conclusions, however, it gave an insight on sympathy might be a key factor in an empathetic textual speech in the Natural Language Processing method of Machine Learning, and outlined that another concept of the Machine Learning, Deep Learning, may offer the optimal solutions in future.
Item Type:Essay (Bachelor)
Clients:
Unknown organization, Enschede, Netherlands
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science BSc (56964)
Link to this item:http://purl.utwente.nl/essays/86908
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