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arXiv · 2510.21659

Smule Renaissance Small: Efficient General-Purpose Vocal Restoration

Yongyi Zang·Chris Manchester·David Young·Ivan Ivanov·Jeffrey Lufkin·Martin Vladimirov·PJ Solomon·Svetoslav Kepchelev·Fei Yueh Chen·Dongting Cai·Teodor Naydenov·Randal Leistikow
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Abstract

Vocal recordings on consumer devices commonly suffer from multiple concurrent degradations: noise, reverberation, band-limiting, and clipping. We present Smule Renaissance Small (SRS), a compact single-stage model that performs end-to-end vocal restoration directly in the complex STFT domain. By incorporating phase-aware losses, SRS enables large analysis windows for improved frequency resolution while achieving 10.5x real-time inference on iPhone 12 CPU at 48 kHz. On the DNS 5 Challenge blind set, despite no speech training, SRS outperforms a strong GAN baseline and closely matches a computationally expensive flow-matching system. To enable evaluation under realistic multi-degradation scenarios, we introduce the Extreme Degradation Bench (EDB): 87 singing and speech recordings captured under severe acoustic conditions. On EDB, SRS surpasses all open-source baselines on singing and matches commercial systems, while remaining competitive on speech despite no speech-specific training. We release both SRS and EDB under the MIT License.

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Yongyi Zang, Chris Manchester, David Young, Ivan Ivanov, Jeffrey Lufkin, Martin Vladimirov, PJ Solomon, Svetoslav Kepchelev, Fei Yueh Chen, Dongting Cai, Teodor Naydenov, Randal Leistikow. 2025-10-24. Smule Renaissance Small: Efficient General-Purpose Vocal Restoration. https://arxiv.org/abs/2510.21659

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