The paper presents an evaluation of popular audio inpainting methods based on autoregressive modelling, namely, extrapolation-based and Janssen methods. A novel variant of the Janssen method suitable for gap inpainting is also proposed. The main differences between the particular popular approaches are pointed out, and a mid-scale computational experiment is presented. The results demonstrate the importance of the choice of the AR model estimator and the suitability of the new gap-wise Janssen method.

翻译：本文评估了基于自回归建模的两种主流音频修复方法，即外推法和Janssen法，并提出了一种适用于缺口修复的Janssen方法新变体。研究指出了各主流方法之间的主要差异，并通过中等规模的计算实验进行验证。结果表明，自回归模型估计器的选择至关重要，且新提出的缺口式Janssen方法具有显著适用性。