标题： 盲音频带宽扩展：一种基于扩散的零样本方法 显示英文标题

标题： Blind Audio Bandwidth Extension: A Diffusion-Based Zero-Shot Approach

摘要： 音频带宽扩展涉及从带限观测中现实地重建高频频谱。 在低通退化未知的情况下，例如在恢复历史音频录音时，这成为一个盲问题。 本文介绍了一种称为BABE（盲音频带宽扩展）的新方法，在零样本设置下解决盲问题，利用预训练无条件扩散模型的生成先验。 在推理过程中，BABE使用扩散后验采样的广义版本，其中退化算子未知但被参数化并迭代推断。 所提出的方法通过客观和主观指标进行评估，结果表明BABE超越了最先进的盲带宽扩展基线，并在使用合成数据测试时与知情方法相比表现出有竞争力的性能。 此外，BABE在增强真实历史录音时表现出强大的泛化能力，有效重建缺失的高频内容，同时保持与原始录音的一致性。 主观偏好测试证实BABE显著提高了历史音乐录音的音频质量。 使用所提出方法恢复的历史录音示例可在配套网页上找到： (http://research.spa.aalto.fi/publications/papers/ieee-taslp-babe/) 显示英文摘要

摘要： Audio bandwidth extension involves the realistic reconstruction of high-frequency spectra from bandlimited observations. In cases where the lowpass degradation is unknown, such as in restoring historical audio recordings, this becomes a blind problem. This paper introduces a novel method called BABE (Blind Audio Bandwidth Extension) that addresses the blind problem in a zero-shot setting, leveraging the generative priors of a pre-trained unconditional diffusion model. During the inference process, BABE utilizes a generalized version of diffusion posterior sampling, where the degradation operator is unknown but parametrized and inferred iteratively. The performance of the proposed method is evaluated using objective and subjective metrics, and the results show that BABE surpasses state-of-the-art blind bandwidth extension baselines and achieves competitive performance compared to informed methods when tested with synthetic data. Moreover, BABE exhibits robust generalization capabilities when enhancing real historical recordings, effectively reconstructing the missing high-frequency content while maintaining coherence with the original recording. Subjective preference tests confirm that BABE significantly improves the audio quality of historical music recordings. Examples of historical recordings restored with the proposed method are available on the companion webpage: (http://research.spa.aalto.fi/publications/papers/ieee-taslp-babe/)