论文标题
通过高斯工艺建模的低频脉冲降解的贝叶斯恢复音频的恢复
Bayesian Restoration of Audio Degraded by Low-Frequency Pulses Modeled via Gaussian Process
论文作者
论文摘要
当用机械设备重现旧乙烯基和留声机记录时发现的一个常见缺陷是由臂针系统相互作用引起的,具有明显的低频含量,并在媒体表面上具有深划痕甚至破裂。以前的抑制录音数字的方法取决于对脉冲位置的先前估计,通常是通过启发式方法执行的。本文提出了一种能够共同估计脉冲位置的新型贝叶斯方法。插入启动脉搏的强不连续性的几乎歼灭信号;并通过简单的高斯过程估算长脉冲尾巴,从而使其被损坏的信号抑制。 Markov-Chain Monte Carlo(MCMC)算法也探索了模型参数的后验分布。对照实验表明,所提出的方法虽然需要较少的用户干预,但可感知结果与以前的方法相似,并且在处理自然降级的信号时表现良好。
A common defect found when reproducing old vinyl and gramophone recordings with mechanical devices are the long pulses with significant low-frequency content caused by the interaction of the arm-needle system with deep scratches or even breakages on the media surface. Previous approaches to their suppression on digital counterparts of the recordings depend on a prior estimation of the pulse location, usually performed via heuristic methods. This paper proposes a novel Bayesian approach capable of jointly estimating the pulse location; interpolating the almost annihilated signal underlying the strong discontinuity that initiates the pulse; and also estimating the long pulse tail by a simple Gaussian Process, allowing its suppression from the corrupted signal. The posterior distribution for the model parameters as well for the pulse is explored via Markov-Chain Monte Carlo (MCMC) algorithms. Controlled experiments indicate that the proposed method, while requiring significantly less user intervention, achieves perceptual results similar to those of previous approaches and performs well when dealing with naturally degraded signals.