BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio Reconstruction

Haoran Wang, Jiatong Shi, Jinchuan Tian, Bohan Li, Kai Yu, Shinji Watanabe


Abstract
Neural audio codecs have recently enabled high-fidelity reconstruction at high compression rates, especially for speech. However, speech and non-speech audio exhibit fundamentally different spectral characteristics: speech energy concentrates in narrow bands around pitch harmonics (80-400 Hz), while non-speech audio requires faithful reproduction across the full spectrum, particularly preserving higher frequencies that define timbre and texture. This poses a challenge—speech-optimized neural codecs suffer degradation on music or sound. Treating the full spectrum holistically is suboptimal: frequency bands have vastly different information density and perceptual importance by content type, yet full-band approaches apply uniform capacity across frequencies without accounting for these acoustic structures. To address this gap, we propose **BSCodec** (Band-Split Codec), a novel neural audio codec architecture that splits the spectral dimension into separate bands and compresses each band independently. Experimental results demonstrate that BSCodec achieves superior reconstruction over baselines across sound and music, while maintaining competitive quality in the speech domain, when trained on the same combined dataset of speech, music and sound. Downstream benchmark tasks further confirm that BSCodec shows strong potential for use in downstream applications.
Anthology ID:
2026.findings-eacl.245
Volume:
Findings of the Association for Computational Linguistics: EACL 2026
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Vera Demberg, Kentaro Inui, Lluís Marquez
Venue:
Findings
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Publisher:
Association for Computational Linguistics
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Pages:
4685–4697
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URL:
https://preview.aclanthology.org/ingest-eacl/2026.findings-eacl.245/
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Cite (ACL):
Haoran Wang, Jiatong Shi, Jinchuan Tian, Bohan Li, Kai Yu, and Shinji Watanabe. 2026. BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio Reconstruction. In Findings of the Association for Computational Linguistics: EACL 2026, pages 4685–4697, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio Reconstruction (Wang et al., Findings 2026)
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