首页> 外文会议>53rd International Symposium ELMAR-2011 >Elimination of unwanted signals in audio materials using wavelet transform
【24h】

Elimination of unwanted signals in audio materials using wavelet transform

机译:使用小波变换消除音频材料中的有害信号

获取原文

摘要

As a sound engineer, employed at Croatian Radio, I realized that the tools for the reconstruction and restoration of old recordings (or damaged recordings) are insufficient and at least they have deficient analyzing method. Orthogonal frequency-based systems, such as the DFT do not offer a good insight into the temporal localization of unwanted parts of the audio material such as pulse-formed signal (e.g., clicks). In this search for such a tool, I reached for the discrete wavelet transformation (DWT) which is realized by double decomposition in order to obtain wavelet coefficients and a graphic depiction of the coefficients. Distortion is measured with according mean square error (MSE) and it is compared with the number of discarded wavelet coefficients. It is also done the comparison between DWT and the results obtained with frequency based systems based on discrete Fourier transform (DFT). After being performed on an arbitrary mathematical function, the wavelet transform is applied on a sound example. (Wave 22.05 kHz, 8 bit). It is shown that DWT is dealing very well with both, noise and discrete disturbance which are the most common problems in the daily work with audio material.
机译:作为克罗地亚广播电台的一名音响工程师,我意识到用于重建和恢复旧唱片(或损坏的唱片)的工具是不够的,至少它们的分析方法不足。诸如DFT之类的基于正交频率的系统无法很好地洞察音频材料中不需要部分的时间定位,例如脉冲形成的信号(例如咔嗒声)。在寻找这种工具的过程中,我找到了离散小波变换(DWT),该方法通过双重分解实现,以获得小波系数和系数的图形表示。用均方根误差(MSE)测量失真,并将其与舍弃的小波系数的数量进行比较。还将DWT与使用基于离散傅里叶变换(DFT)的基于频率的系统获得的结果进行比较。在对任意数学函数执行了小波变换之后,将小波变换应用于声音示例。 (波22.05 kHz,8位)。结果表明,DWT可以很好地处理噪声和离散干扰,这是音频材料日常工作中最常见的问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号