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A Potentially More Humane Way to Let the Machines In
The Post writes that we bring a scientific approach to aligning AI with well-being, with "a high degree of psychology research to accompany those ethical goals" and "an ethics committee with many heavy-hitters in the field of emotional and ethical AI."
Read more about Hume AI and The Hume Initiative in The Washington Post.
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Behind Hume’s Expression Measurement Models for Face and Voice
Editor's note: This post covers the science, development and evaluation of Hume’s state of the art Expression API, that enables developers to enrich their applications or research pipelines with real-time measurement of voice and facial expressions. Facial expressions and vocal tone are central to how we communicate. They convey emotions such as amusement, interest, frustration, and surprise, often without naming those feelings in words. Understanding these signals is part of how we connect with one another and respond to what others express.
Oct 6, 2026
Evaluating Google’s multi-speaker TTS: A case study in why private evaluations matter
Text-to-speech systems were originally built to read text aloud in a single voice. As voice AI expands into audiobooks, game dialogue, and advertising, these systems are being asked to do more: generate conversations between multiple speakers. That takes more than generating two distinct voices and stitching their lines together. The speakers need to sound like they are responding to one another, with natural timing, changes in tone, and smooth handoffs. Each voice must remain distinct and consistent while contributing to a believable conversation.
Sharath Rao, Kimberly Lo, Alice Baird / Sep 29, 2026