A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study
Min Lyu, Lixin Tan, Jun Xiao, Heqing Huang, Fangjian Liu, Jiahui Qi, Tian Huang, Jinyu Lei, Zhihui Zhao, Tianxiang Jiang, Zhu Liu, Xueqian Wang, Jiang Zhong, Zhengzhi Feng, Ivan Steenstra · 2026
Read A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study by Min Lyu, Lixin Tan, Jun Xiao, Heqing Huang, Fangjian Liu, Jiahui Qi, Tian Huang, Jinyu Lei, Zhihui Zhao, Tianxiang Jiang, Zhu Liu, Xueqian Wang, Jiang Zhong, Zhengzhi Feng, Ivan Steenstra (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13577659.txt.
Description
Min Lyu and co-authors test whether the sound of a student's voice, caught on a phone, can flag thoughts of suicide. Their 2026 study starts from a hard fact: students may hide such thoughts on forms, or share them too late. A cheap, quick screen could help campus services reach them sooner.
Ninety-six students took part, half with such thoughts and half without, after checks by clinicians. Each read sixteen set sentences into a phone app. Software pulled hundreds of sound traits from each clip, and seven learning methods were trained to sort the two groups. To keep the test fair, all clips from one speaker stayed in the same test fold. The paper reports how the models were built and checked.
Catalog record
| CREATOR | Min Lyu, Lixin Tan, Jun Xiao, Heqing Huang, Fangjian Liu, Jiahui Qi, Tian Huang, Jinyu Lei, Zhihui Zhao, Tianxiang Jiang, Zhu Liu, Xueqian Wang, Jiang Zhong, Zhengzhi Feng, Ivan Steenstra |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 40 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |