# Artificial Intelligence for Suicide Assessment using Audiovisual Cues: A Review

arXiv: https://arxiv.org/abs/2201.09130 · HTML: https://mlsanity.com/paper/2201.09130/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 80 references that are in the map.
- First posted on arXiv 22 Jan 2022.

## Builds on (most cited first, 6 of 6)

- [AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition](https://mlsanity.com/paper/1907.11510/) (2019)
- [Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications](https://mlsanity.com/paper/1910.12611/) (2019)
- [Deep Learning for Depression Recognition with Audiovisual Cues: A Review](https://mlsanity.com/paper/2106.00610/) (2021)
- [Automatic prediction of suicidal risk in military couples using multimodal interaction cues from couples conversations](https://mlsanity.com/paper/1911.11927/) (2019)
- [A Survey of Hybrid Human-Artificial Intelligence for Social Computing](https://mlsanity.com/paper/2103.15558/) (2021)
- [A Comparative Study of Glottal Source Estimation Techniques](https://mlsanity.com/paper/2001.00840/) (2019)

## Built on by (most cited first, 8 of 8)

- [Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing](https://mlsanity.com/paper/2205.02764/) (2022)
- [Spontaneous Speech-Based Suicide Risk Detection Using Whisper and Large Language Models](https://mlsanity.com/paper/2406.03882/) (2024)
- [Selective Task offloading for Maximum Inference Accuracy and Energy efficient Real-Time IoT Sensing Systems](https://mlsanity.com/paper/2402.16904/) (2024)
- [Adapting Mental Health Prediction Tasks for Cross-lingual Learning via Meta-Training and In-context Learning with Large Language Model](https://mlsanity.com/paper/2404.09045/) (2024)
- [Maximizing UAV Fog Deployment Efficiency for Critical Rescue Operations](https://mlsanity.com/paper/2402.16052/) (2024)
- [Language-Agnostic Suicidal Risk Detection Using Large Language Models](https://mlsanity.com/paper/2505.20109/) (2025)
- [Dynamic Fusion Multimodal Network for SpeechWellness Detection](https://mlsanity.com/paper/2508.18057/) (2025)
- [Tri-Modal Severity Fused Diagnosis across Depression and Post-traumatic Stress Disorders](https://mlsanity.com/paper/2510.20239/) (2025)

## Abstract (arXiv)

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.