TACSTechnology and Application of Computer Science2998-89262998-8934Art and Design10.61369/TACS.2025010025Article基于语音特征的抑郁症 AI 筛查模型的研究与设计https://artdesignp.com/journal/TACS/2/1/10.61369/TACS.2025010025张宵,白雪俊,唐琳,张乐伊,苏雪,王金社,沈宇星,陈彦华2025212025-01-14针对传统抑郁症量表 [2] 筛查效率低的问题，本研究提出基于语音特征的自动筛查模型。通过采集 200例临床患者和健康个体的语音样本，经预处理提取特征后，构建结合 LSTM 时间建模与 Attention 机制的深度学习模型。测试显示模型准确率达 84.62%，F1分数 0.86，在效率和一致性上优于传统量表。抑郁症,语音特征,LSTM-Attention 机制,深度学习,心理健康筛查

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