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A Conversational Model for the Reminiscence Therapy of Patients with Early Stage of Alzheimer

Reminiscence therapy is a treatment that helps mitigate unstable psychological states in patients with Alzheimer's disease, where past experiences are evoked through conversations between the patient and their caregiver, stimulating autobiographical episodic memory. It is highly recommended that people with Alzheimer's receive this type of therapy constantly. This article describes the initial work in the development and implementation of a conversational model that can support caregivers of patients with this type of dementia to provide therapy periodically and enhance the benefits it offers. It is intended that the model allows generating personalized conversations between a prototype of the conversational system and patients. The proposed model collects patient information related to their preferences, history and lifestyle to personalize the conversation according to the profile of them. The modules that integrate this architecture are the following: Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Dialog Management (DM), Dialog Model, Natural Language Generation (NLG) y Text-to-Speech (TTS).