High-Fidelity Speech Enhancement via Discrete Audio Tokens

• URL: http://arxiv.org/abs/2510.02187v1
• Date: Thu, 02 Oct 2025 16:38:05 GMT
• Title: High-Fidelity Speech Enhancement via Discrete Audio Tokens
• Authors: Luca A. Lanzendörfer, Frédéric Berdoz, Antonis Asonitis, Roger Wattenhofer,
• Abstract summary: DAC-SE1 is a language model-based SE framework leveraging discrete high-resolution audio representations.<n>Our experiments show that DAC-SE1 surpasses state-of-the-art autoregressive SE methods on both objective perceptual metrics and in a MUSHRA human evaluation.
• Score: 35.61634772862795
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent autoregressive transformer-based speech enhancement (SE) methods have shown promising results by leveraging advanced semantic understanding and contextual modeling of speech. However, these approaches often rely on complex multi-stage pipelines and low sampling rate codecs, limiting them to narrow and task-specific speech enhancement. In this work, we introduce DAC-SE1, a simplified language model-based SE framework leveraging discrete high-resolution audio representations; DAC-SE1 preserves fine-grained acoustic details while maintaining semantic coherence. Our experiments show that DAC-SE1 surpasses state-of-the-art autoregressive SE methods on both objective perceptual metrics and in a MUSHRA human evaluation. We release our codebase and model checkpoints to support further research in scalable, unified, and high-quality speech enhancement.

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