30-second voice recording predicts biological aging, finds npj Aging study
segal_eran · x · 2026-09-20
Eran Segal's team published a new npj Aging paper showing a 30-second voice recording captures a signature of biological aging. Using 7,000 participants from the Human Phenotype Project, they trained voice-based age models to predict chronological age. The resulting "Voice Age" was among the strongest single-modality aging clocks and added information beyond metabolomics, imaging, physiology and lifestyle.
A higher Voice Age gap was associated with adiposity, sleep-disordered breathing, poorer nocturnal oxygenation, and liver-related traits — suggesting voice as a simple, scalable biomarker of accelerated biological aging.
More from Research
- WindTunnel benchmark: WebMCP makes browser agents 2.5-7.5x faster, 3-47x cheaper — FinanceYF5 · 2026-09-20
- Gary Marcus disputes LLM 'pain direction' paper: language clusters don't mean suffering — anilkseth · 2026-09-20
- MatSemNet uses LLMs to mine 700+ papers, modeling reaction pathways as sequences for catalyst discovery — bravo_abad · 2026-09-20
- Smart Zoi runs 50 AI NPCs in real time with a fine-tuned 1B SLM, LIFT hits 100+ citations — Kangwook_Lee · 2026-09-20
- LlamaIndex benchmarks 100+ models on document parsing with ParseBench — solyarisoftware · 2026-09-20
- ICLR gets record submissions; authors' journal spam emails hit records too — wandedob · 2026-09-20