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New Enhancements to the Automatic Noise Removal (ANR) System Utilizing Improved Noise Statistics and Multi-Band Processing

机译:利用改进的噪声统计和多频带处理的自动噪声去除(ANR)系统的新增强功能

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We recently introduced a novel Automatic Noise Reduction (ANR) algorithm for the removal of wideband stationary/non-stationary noise from audio [1]. Current noise reduction techniques exhibit certain undesirable characteristics. Distortion and/or alteration of the audio characteristics is a common problem. User intervention in identifying the noise profile is sometimes necessary. ANR uses a novel framework employing dominant component subtraction and restoration and performs better than conventional techniques in subjective tests. Here we describe three enhancements to ANR. The first of these increases the level of noise removal for the special case of stationary background noise. The second is a new tool for improving the temporal envelope coherence and yields additional noise removal. The third is a multi-band processing tool for conditioning time-frequency envelope for reduced listener fatigue.
机译:我们最近推出了一种新的自动降噪(ANR)算法,用于从音频[1]中移除宽带静止/非静止噪声。电流降噪技术表现出某些不希望的特性。音频特征的失真和/或改变是一个常见问题。有时需要用户干预识别噪声分布。 ANR使用采用主体分量减法和恢复的新颖框架,并且比主观测试中的传统技术更好地执行。在这里,我们描述了对ANR的三种增强功能。其中的第一个增加了静止背景噪声特殊情况的噪声清除水平。第二种用于改善时间包络相干性的新工具,并产生额外的噪声去除。第三是用于调节时频包络的多频带处理工具,用于减少听众疲劳。

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