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arXiv · 2610.15464

The NPU-ASLP System for Music Restoration in the CCF-AATC 2026 Challenge

Zeyu Zhu·Yike Zhu·Xingchen Li·Chaoren Yu·Jingyi Wang·Yurun Li·Jierui Guo·Chunjiang He·Lei Xie
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Abstract

This paper presents the NPU-ASLP music restoration system developed for Track 1 of the China Computer Federation (CCF) Advanced Audio Technology Competition (AATC) 2026 Challenge. The task aims to recover clean music from mobile-device-captured recordings affected by coupled degradations from playback devices, acoustic propagation, environmental noise and recording terminals. System development is further constrained by limited and imperfectly aligned real data pairs and a strict model-complexity budget. In our system, we adopt TF-MoE as the backbone for its dual-axis modeling of cross-band and temporal dependencies, whose Top-1 routing activates a single expert per token to bound computation under the strict budget. We extend it with two task-specific adaptations: a scale-aware encoder and a complex mapping decoder. The former encodes normalized complex spectra jointly with per-band log-RMS to preserve the band-energy cues discarded by band-wise normalization. The latter directly estimates the clean complex spectrum rather than masking the input, thereby repairing coupled degradations. To address the limited, imperfectly aligned real recordings, we further build a challenge-calibrated playback--propagation--recording simulator that generates 1,572.12 h of sample-aligned data across 202 acoustic conditions. The final system contains 2.951M parameters and requires 82.659 GMACs for a 10-s input. On the official blind test, it achieved -49.067 dB SI-SNR, 1.273 LSD, 2.540 FAD, and 3.495 ViSQOL. It ranked third in LSD, FAD, and ViSQOL and received the third prize in the challenge.

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Zeyu Zhu, Yike Zhu, Xingchen Li, Chaoren Yu, Jingyi Wang, Yurun Li, Jierui Guo, Chunjiang He, Lei Xie. 2026-10-11. The NPU-ASLP System for Music Restoration in the CCF-AATC 2026 Challenge. https://arxiv.org/abs/2610.15464

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