计算机应用 ›› 2014, Vol. 34 ›› Issue (5): 1391-1396.DOI: 10.11772/j.issn.1001-9081.2014.05.1391

• 人工智能 • 上一篇    下一篇

基于Radon和平移不变性小波变换的鸟类声音识别

周晓敏,李应   

  1. 福州大学 数学与计算机科学学院,福州 350108
  • 收稿日期:2013-10-24 修回日期:2013-12-23 出版日期:2014-05-01 发布日期:2014-05-30
  • 通讯作者: 李应
  • 作者简介:周晓敏(1989-),女,福建漳州人,硕士研究生,主要研究方向:声音识别;李应(1964-),男,福建福清人,教授,博士,主要研究方向:声音识别、多媒体数据检索、信息安全。
  • 基金资助:

    国家自然科学基金资助项目

Bird sounds recognition based on Radon and translation invariant discrete wavelet transform

ZHOU Xiaomin,LI Ying   

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou Fujian 350108, China
  • Received:2013-10-24 Revised:2013-12-23 Online:2014-05-01 Published:2014-05-30
  • Contact: LI Ying

摘要:

针对低信噪比(SNR)环境下鸟叫声识别率不够高的问题,提出一种对声谱图进行Radon变换(RT)和平移不变性离散小波变换(TIDWT)的抗噪型鸟类声音识别技术。首先,使用改进的多频带谱减法对鸟叫声进行降噪处理;其次,利用短时能量检测降噪后的鸟叫声的静音段,并去除静音段;接着,将去除静音段的声音信号转化为声谱图,并对声谱图进行RT和TIDWT,提取特征值;最后,采用支持向量机(SVM)分类器对提取的特征值进行分类识别。实验结果表明,该方法在信噪比为10dB及以下仍可以达到较好的识别效果。

Abstract:

To improve the accuracy of bird sounds recognition in low Signal-to-Noise Ratio (SNR) environment, a new bird sounds recognition technology based on Radon Transform (RT) and Translation Invariant Discrete Wavelet Transform (TIDWT) from spectrogram after the noise reduction was proposed. First, an improved multi-band spectral subtraction method was presented to reduce the background noise. Second, short-time energy was used to detect silence of clean bird sound, and the silence was removed. Then, the bird sound was translated into spectrogram, RT and TIDWT were used to extract features. Finally, classification was achieved by Support Vector Machine (SVM) classifier. The experimental results show that the method can achieve better recognition effect even the SNR belows 10dB.

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