Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation
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Computer Science > Artificial Intelligence
Title:Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation
Abstract:Conversational speech depends on dialogue context and the listener's immediately preceding behavior. We propose ReACT-TTS, a two-stage framework that uses a one-second pre-response listener facial sequence to plan the next utterance's emotion and prosody before speech realization. On a strict dyadic MELD protocol, Temporal conditioning yields higher mean macro-F1 and VAD concordance than Text-only across ten seeds, while accuracy remains essentially unchanged. Ablations show that temporal modeling performs best among the visual variants and that an explicit early-to-late difference is unnecessary; correct listener reactions also outperform cyclic mismatches on average. In a contextual-appropriateness study with 20 speech researchers, 76% of judgments prefer Temporal, 9% Text-only, and 15% report no preference. We further connect the predicted response style to a Grad-TTS backbone for end-to-end speech realization. Overall, the results support pre-response listener dynamics as complementary cues for conversational response planning. The source code is available at this https URL.
| Comments: | 15 pages, 2 figures, 2026 ECCV Workshop (11th ABAW) Best Student Paper Award |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV); Sound (cs.SD) |
| Cite as: | arXiv:2609.21683 [cs.AI] |
| (or arXiv:2609.21683v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2609.21683
arXiv-issued DOI via DataCite (pending registration)
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