Abstract

This paper focuses on home smart voice devices to address the problems of traditional mental health diagnosis and evaluation (e.g., the inability to monitor, analyze and assess mental health in real-time and the heavy reliance on psychologists and counselors for judgment). It constructs a model for monitoring, examining, and evaluating children's mental health using interactive communication and voice recordings between children and intelligent voice devices. The model uses techniques such as natural language processing and data mining based on a random forest algorithm. Meanwhile, this paper explores and investigates the feasibility of implementing the model on the ground in terms of technology development and technology preference.

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