Back
Sound of Aging: Large-Scale Evidence for a Voice-Based Biological Clock
Krongauz, D.; Marmor, Y.; Zulti, A.; Godneva, A.; Weinberger, A.; Segal, E.
2026-04-06
health informatics
10.64898/2026.04.05.26350190
medRxiv
Show abstract
Using 30-second voice recordings from 7,081 adults aged 40-70, we trained gender-specific models to estimate voice-predicted age (Voice Age). Voice Age correlated with chronological age comparably to established omic and physiological aging clocks, while capturing an independent dimension of biological aging. Accelerated vocal aging showed association with higher adiposity, impaired sleep physiology, and cardiometabolic risk markers, supporting voice as a scalable, non-invasive functional aging biomarker.
Matching journals
●Non-profit
◐University press
○Commercial
The top 4 journals account for 50% of the predicted probability mass.
1
Nature Communications
○
4913 papers in training set
Top 2%
22.9%
2
Nature Aging
○
51 papers in training set
Top 0.1%
18.9%
3
Aging Cell
○
144 papers in training set
Top 0.8%
7.3%
4
Science Translational Medicine
●
111 papers in training set
Top 0.5%
4.4%
50% of probability mass above
5
Advanced Science
○
249 papers in training set
Top 4%
4.4%
6
Science Advances
●
1098 papers in training set
Top 3%
4.2%
7
Nature Medicine
○
117 papers in training set
Top 1%
3.1%
8
Scientific Reports
○
3102 papers in training set
Top 41%
3.1%
9
Communications Biology
○
886 papers in training set
Top 3%
2.8%
10
eBioMedicine
○
130 papers in training set
Top 0.6%
2.4%
11
Med
○
38 papers in training set
Top 0.3%
1.7%
12
Nature Biomedical Engineering
○
42 papers in training set
Top 0.8%
1.7%
13
npj Aging
○
15 papers in training set
Top 0.7%
1.2%
14
Nature
○
575 papers in training set
Top 13%
1.1%
15
Cell Reports
○
1338 papers in training set
Top 30%
0.9%
16
Cell Metabolism
○
49 papers in training set
Top 2%
0.9%
17
European Respiratory Journal
●
54 papers in training set
Top 2%
0.8%
18
Science
●
429 papers in training set
Top 19%
0.8%
19
Nature Metabolism
○
56 papers in training set
Top 2%
0.8%
20
Cell Reports Medicine
○
140 papers in training set
Top 8%
0.8%
21
eLife
●
5422 papers in training set
Top 57%
0.8%