用人工智能 (AI) 驱动的技术来管理儿科语音和语言治疗:范围审查
Milad Dadgar1, Cathy Ennis2, Kesego Mokgosi1
1School of Computer Science, Technological University Dublin, Ireland.
Digital health
|November 10, 2025
概括
人工智能和机器学习正在为患有语音障碍 (SSD) 的儿童增强语音语言治疗 (SLT). 这些人工智能驱动的工具提供个性化治疗,并改善治疗师的诊断支持.
科学领域:
- 语音和语言治疗治疗
- 医疗保健中的人工智能
- 儿科语言障碍 儿科语言障碍
背景情况:
- 语音音障碍 (SSD) 是一个重大挑战,原因是儿童的语音语言治疗 (SLT) 服务有限.
- 技术,特别是人工智能和机器学习 (ML),提供了创新的解决方案,以支持儿童,家长和治疗师在SLT过程中.
- 自动语音识别和音频处理是推动SLT进步的关键AI技术.
研究的目的:
- 对利用人工智能和机器学习技术管理SSD儿童SLT过程的研究进行范围审查.
- 检查自动语音识别和音频处理在当前SLT实践中的作用.
- 确定人工智能辅助SLT模型的有效性和潜力.
主要方法:
- 在2025年2月3日,在五个主要数据库 (PubMed,Scopus,ScienceDirect,ACM数字图书馆,IEEE Xplore) 进行了系统搜索.
- 搜索遵循系统性审查的首选报告项目和范围审查的元分析 (PRISMA-ScR) 的指导方针.
- 在 188 项已识别的研究中,有 30 项符合纳入审查的资格标准.
主要成果:
- 研究主要使用深度神经网络,ML分类器,声学特征和音频处理来检测SSD.
- 人工智能应用程序有效地支持治疗师诊断SSD.
- 基于计算机的工具通过个性化治疗计划和实时反来证明对儿童的参与度更高,有助于监测进展.
结论:
- 人工智能辅助的SLT模型在改善SLT流程方面显示出显著的有效性和潜力.
- 目前用于SLT的AI应用中的差距包括数据隐私,可访问性和需要强大的临床验证.
- 未来的研究应该专注于解决这些挑战,以充分实现人工智能在儿科SLT中的好处.
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