AI & ML
Prime-EVC: One-Step Expressive Emotional Voice Conversion via Emotion-Primed Flow Matching
arXiv cs.SD0 views
arXiv:2610.16036v1 Announce Type: new Abstract: Recent diffusion- and conditional flow matching (CFM)-based emotional voice conversion (EVC) systems achieve strong conversion quality. However, they typically rely on multiple sampling steps, because the conditioning specifies which emotion to impose while its acoustic realization is left to the sampler. In this paper, we propose Prime-EVC, a one-step expressive EVC architecture based on emotion-primed flow matching. Our key idea is to reallocate the emotional conversion between the conditioning and the sampler: a FiLM-fused speaker-emotion style, an emotional variance adaptor, and direct emotion and spectro-temporal supervision assemble an emotion-rich conditioning upstream, rendering the residual conversion left to the CFM decoder attainable within one Euler step. Experiments on the ESD corpus demonstrate that single-step Prime-EVC surpasses five representative EVC systems on every quality metric and exceeds 4- and 100-step DurFlex-EVC in subjective naturalness and emotion while running 3.4--50 times faster than both.
Source:https://arxiv.org/abs/2610.16036PreviousTASTE: Taxonomy-Aware Symbolic Piano Generation from Textual DescriptionNextAdaptive Compression and Targeted Perturbation: A Unified Framework for Generalized Audio Deepfake Detection
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