When Voice AI Has the Evidence but Follows the Text
TL;DR for operators Audio AI can retain information about a speaker’s voice and still produce an answer that follows a contradictory written description. In controlled experiments, audio language models favored conflicting textual claims at a reported mean rate of 78%, rising to 86% when sarcasm and pacing were excluded. The research traces this failure to how textual information influences downstream representations, rather than simply to missing acoustic information. A targeted attention intervention substantially reduced text dominance during free-form generation in one model, but the benefit depended on intervention placement and evaluation format. ...