论文标题
使用视听提示进行自杀评估的人工智能：评论
Artificial Intelligence for Suicide Assessment using Audiovisual Cues: A Review
论文作者
论文摘要
自杀死亡是全球第七次主要死亡原因。最近的人工智能（AI）的进步，特别是图像和语音处理中的AI应用程序，为彻底改变了自杀风险评估的机会。随后，我们目睹了快速增长的研究文献，该文献适用于AI提取精神疾病评估的视听非语言提示。然而，尽管抑郁症状与自杀行为和非语言提示之间存在明显差异，但最近的大多数著作都集中在抑郁症上。本文回顾了最近的著作，这些著作通过视听特征分析研究了自杀构想和自杀行为检测，主要是自杀语音/语音声学特征分析和自杀视觉提示。自杀评估是一个有希望的研究方向，仍处于早期阶段。因此，缺乏大型数据集，可用于训练机器学习和深度学习模型，这些模型被证明在其他类似的任务中有效。
Death by suicide is the seventh leading death cause worldwide. The recent advancement in Artificial Intelligence (AI), specifically AI applications in image and voice processing, has created a promising opportunity to revolutionize suicide risk assessment. Subsequently, we have witnessed fast-growing literature of research that applies AI to extract audiovisual non-verbal cues for mental illness assessment. However, the majority of the recent works focus on depression, despite the evident difference between depression symptoms and suicidal behavior and non-verbal cues. This paper reviews recent works that study suicide ideation and suicide behavior detection through audiovisual feature analysis, mainly suicidal voice/speech acoustic features analysis and suicidal visual cues. Automatic suicide assessment is a promising research direction that is still in the early stages. Accordingly, there is a lack of large datasets that can be used to train machine learning and deep learning models proven to be effective in other, similar tasks.
