SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering

TL;DR

SonicMaster is a unified generative model that uses text-based instructions to restore and master music recordings, improving audio quality across various artifact types with objective and subjective validation.

Contribution

It introduces the first model that combines music restoration and mastering in a single framework conditioned on natural language instructions.

Findings

SonicMaster significantly improves sound quality across artifact categories.

Listeners prefer SonicMaster's outputs over baseline methods.

The model effectively applies targeted enhancements guided by text prompts.

Abstract

Music recordings often suffer from audio quality issues such as excessive reverberation, distortion, clipping, tonal imbalances, and a narrowed stereo image, especially when created in non-professional settings without specialized equipment or expertise. These problems are typically corrected using separate specialized tools and manual adjustments. In this paper, we introduce SonicMaster, the first unified generative model for music restoration and mastering that addresses a broad spectrum of audio artifacts with text-based control. SonicMaster is conditioned on natural language instructions to apply targeted enhancements, or can operate in an automatic mode for general restoration. To train this model, we construct the SonicMaster dataset, a large dataset of paired degraded and high-quality tracks by simulating common degradation types with nineteen degradation functions belonging to five enhancements groups: equalization, dynamics, reverb, amplitude, and stereo. Our approach leverages a flow-matching generative training paradigm to learn an audio transformation that maps degraded inputs to their cleaned, mastered versions guided by text prompts. Objective audio quality metrics demonstrate that SonicMaster significantly improves sound quality across all artifact categories. Furthermore, subjective listening tests confirm that listeners prefer SonicMaster's enhanced outputs over other baselines.