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Duplex Cue is introduced, an evaluation of this in-turn adaptation in full-duplex voice agents that separates listener intent from speaker behavior: continuing unchanged, adapting within the turn, or yielding.
The results show that the evaluated baselines can extract some affective signal from speech, but discrete expressed-emotion recognition remains fragile, especially for non-neutral emotions that are often most important in voice agent workflows.
Across systems, WER has little rank agreement with CTEM (Spearman $\rho=-0.28$) or TSR (Spearman $\rho=-0.28$), and even the strongest system leaves nearly one-third of recordings with an unrecovered critical value.
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