综述神经退行性言语障碍的智能分析技术，助力早期诊断与辅助应用。
Overview of Automatic Speech Analysis and Technologies for Neurodegenerative Disorders: Diagnosis and Assistive Applications
- 系统梳理病理性语音检测、识别与可懂度增强方法
- 提出多维度评估体系，涵盖严重程度与可懂度指标
- 适合临床与语音技术交叉研究者参考
针对神经退行性言语障碍，本综述全面总结了当前最先进的病理语音检测、自动语音识别、可懂度增强、严重程度与可懂度评估，以及病理语音数据增强方法。同时指出关键技术挑战，包括鲁棒性、隐私保护与可解释性问题。展望未来方向，强调多模态融合与大语言模型集成对推动该领域发展的潜力。
原文摘要 · Abstract (English)
Advancements in spoken language technologies for neurodegenerative speech disorders are crucial for meeting both clinical and technological needs. This overview paper is vital for advancing the field, as it presents a comprehensive review of state-of-the-art methods in pathological speech detection, automatic speech recognition, pathological speech intelligibility enhancement, intelligibility and severity assessment, and data augmentation approaches for pathological speech. It also highlights key challenges, such as ensuring robustness, privacy, and interpretability. The paper concludes by exploring promising future directions, including the adoption of multimodal approaches and the integration of large language models to further advance speech technologies for neurodegenerative speech disorders.
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