Hume launches the first decision model for voice AI

Hume introduced an audio-native decision model that takes audio, a question and possible answers and returns a probability for each answer, aimed at evaluating speech and sound in voice applications. Hume says the model agrees with the human crowd 70.7% of the time versus 56.5% for a single human rater, and scores an average 0.82 across 10 leading benchmarks at a median latency of 0.23 s per screen. It is offered via a Decision Model API as a decision layer in voice-agent systems alongside speech recognition and generation.