Removal of low frequency transient noise from old recordings using model-based signal separation techniques

S. Godsill, C. H. Tan
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引用次数: 17

Abstract

This paper is concerned with the removal of low frequency transient noise from old gramophone recordings and film sound tracks. Low frequency transients occur as a result of large breakages or discontinuities in the recorded medium which excite a long-term resonance in the playback apparatus. We present a signal separation-based approach to this problem. Audio signals and noise transients are modelled as autoregressive (AR) processes which are additively superimposed to give the observed waveform. A maximum a posteriori method is presented for separation of the two processes. A modification of this scheme allows for modelling of the large discontinuity at the start of each noise transient and successful restorations are demonstrated. A more practical scheme is then developed which uses a Kalman filter to implement the separation. In order to avoid low frequency distortions to the audio signal, the excitation variance of the noise transient model is tapered exponentially to zero away from the discontinuity. The method is fully automated and more practical to implement than existing schemes for removal of such defects. Results indicate a high level of performance.
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使用基于模型的信号分离技术从旧录音中去除低频瞬态噪声
本文研究了旧留声机录音和电影音轨中低频瞬态噪声的去除问题。低频瞬变是由于记录介质的大断裂或不连续而引起的,这在回放装置中激发了长期的共振。我们提出了一种基于信号分离的方法来解决这个问题。音频信号和噪声瞬态被建模为自回归(AR)过程,加性叠加得到观察到的波形。提出了一种最大后验方法来分离这两个过程。该方案的修改允许在每个噪声开始时对大的不连续进行建模,证明了瞬态和成功的恢复。然后开发了一种更实用的方案,使用卡尔曼滤波器来实现分离。为了避免音频信号的低频失真,噪声瞬态模型的激励方差在远离不连续点的情况下呈指数递减至零。该方法是完全自动化的,并且比现有的消除此类缺陷的方案更实用。结果表明了高水平的表现。
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