Junichi Yamagishi
Whether human listeners — or automated detectors — can tell AI-generated speech apart from real human speech, and how that distinguishability changes as speech synthesis improves.
Yamagishi has been the primary organizer of ASVspoof, the international challenge that tracks how well automated systems can detect spoofed or synthetic speech, since the first edition in 2015. The accumulated record from the challenge series is one of the few longitudinal datasets in AI-content-detection that covers an entire technology generation — from early concatenative synthesis to current neural voice cloning. He co-organizes the parallel VoiceMOS challenge for evaluating synthetic-speech quality, which makes him uniquely positioned on both sides of the question: how good has synthesis gotten, and how detectable does that goodness remain. For ai100, as AI engines move toward voice output, this is the methodology stack for evaluating what it sounds like when an LLM speaks.