P2Flow: Phoneme-aware Progressive Flow Matching for Extreme Speech Super-Resolution
Generative models have recently demonstrated considerable promise in speech super-resolution (SSR). Nevertheless, the majority of existing work has concentrated on standard or versatile SSR configurations, leaving the extreme setting with severely limited spectral inputs largely unexplored. In this regime, current approaches exhibit marked performance degradation, underscoring the need for dedicated solutions. To bridge this gap, we introduce P2Flow, a phoneme-aware progressive flow matching (FM) framework designed for extreme SSR with three main strategies. First, our model leverages phonetic information to reconstruct missing spectral components. Furthermore, it employs a progressive ar...
| Authors | Ningyuan Yang, Yize Li, Pu Zhao et al. |
|---|---|
| Primary category | eess.AS |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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