With this AI, your voice could give away your face

In research published on Arxiv, a publishing site for non-peer-reviewed papers, MIT researchers created a way to reconstruct some people's very rough likeness based on a short audio clip. The paper, "Speech2Face: Learning the Face Behind a Voice," explains how they took a dataset made up of millions of clips from YouTube and created a neural network-based model that learns vocal attributes associated with facial features from the videos. Now, when the system hears a new sound bite, the AI can use what it's learned to guess what the face might look like. The researchers, led by MIT postdoctoral student Tae-Hyun Oh, do briefly acknowledge the privacy concerns in the paper, explaining in an "Ethical Consideration" section that Speech2Face was trained to capture visual features like gender and age that are common, and only when there was enough evidence from the voice to do so. In other words, the system is not trying or able to produce images of specific people.