[B]y the time [Ariana] Anderson’s third kid came along, the UCLA computational neuropsychologist realized she had become fluent in baby. Her ear had learned which sounds meant “feed me!” which ones were “change me!” and which ones signaled something more serious: pain. Anderson wondered if she could train an algorithm to do the same thing.

Five years, thousands of howls, and more than 1,700 babies later, Anderson’s AI-powered translator is here. Called Chatterbaby, the free app analyzes changes in frequency and patterns in the sound to silence ratio to tell parents why their kiddo is crying.

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You see, Chatterbaby isn’t just an app designed to help parents, be they deaf, or new, or just overwhelmed and underslept. It’s also a massive data-collecting tool to see if irregularities in cry patterns could carry signals about autism.

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Anderson’s team plans to combine all this data with the audio files to build a machine learning model capable of predicting different kinds of autism from cries alone.

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[A]lgorithms won’t be enough to democratize good outcomes. But they might be a start.

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