精神疾病中的语音分析和语音情绪识别:一个范围审查
Clara Lombardo1, Giulia Esposito2, Silvia Carbone3
1Department "Scienze della Salute", University of Catanzaro, Catanzaro, Italy.
Frontiers in psychology
|November 24, 2025
概括
语音分析,特别是语音情感识别 (SER),对诊断精神障碍有很大的希望. 这种可访问,非侵入性的方法可以识别与疾病相关的特定语音模式,有助于早期发现和个性化治疗.
科学领域:
- 精神病学是一个精神病学.
- 计算语言学 计算语言学
- 机器学习 机器学习
背景情况:
- 精神障碍显著影响情绪调节,需要疾病特异性生物标志物用于早期诊断.
- 应用于语音分析的机器学习为心理健康评估提供了一个有希望的途径.
- 精神疾病中变化的前性情绪表达导致使用语音情绪识别 (SER) 模型来识别精神疾病.
研究的目的:
- 审查语音分析在诊断精神障碍中的应用.
- 专注于使用SER系统检测精神疾病的研究.
主要方法:
- 在PubMed,Scopus和Google Scholar上进行了系统的文献搜索.
- 搜索涵盖了2014年至2024年的出版物.
- 符合纳入标准的12项研究被选中进行审查.
主要成果:
- 语音分析有效地区分患者和健康个体.
- 特定的声音模式与某些精神疾病有关.
- SER系统成功地使用情绪作为检测精神障碍,特别是情绪障碍的中间步骤.
结论:
- 语音信号分析是一种可访问的,非侵入性的精神健康评估方法.
- 这种方法有助于更早地诊断精神障碍.
- 它可以为患者提供更高的治疗个性化.
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