通信学报 ›› 2013, Vol. 34 ›› Issue (8): 120-130.doi: 10.3969/j.issn.1000-436x.2013.08.016

• 学术论文 • 上一篇    下一篇

基于非线性音频特征分类的频带扩展方法

张丽燕,鲍长春,刘鑫,张兴涛   

  1. 北京工业大学 电子信息与控制工程学院 语音与音频信号处理研究室,北京 100124
  • 出版日期:2013-08-25 发布日期:2017-08-31
  • 基金资助:
    国家自然科学基金资助项目;国家自然科学基金资助项目;北京市教育委员会科技发展计划重点基金资助项目;北京市自然科学基金资助项目;北京市属高等学校人才强教计划基金资助项目;北京工业大学第九届研究生科技基金资助项目

Bandwidth extension method based on nonlinear audio characteristics classification

Li-yan ZHANG,Chang-chun BAO,Xin LIU,Xing-tao ZHANG   

  1. Speech and Audio Signal Processing Lab,School of Electronic Information and Control Engineering,Beijing University of Technology,Beijing 100124,China
  • Online:2013-08-25 Published:2017-08-31
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China;Beijing Natural Science Foundation Program and Scientific Research Key Program of Beijing Municipal Commission of Education;The Natural Science Foundation of Beijing;The Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality;The 9th Postgraduate Science Foundation of Beijing University of Technology

摘要:

提出了一种基于非线性音频分类的频带扩展方法,即利用递归图和定量递归分析将音频信号的时间序列分成4类,并分别采用4种方法恢复高频频谱细节,最终利用高斯混合模型和基于软判决的码书映射调整频谱包络和能量增益。主客观测试表明,该方法优于传统的盲目式频带扩展方法,且应用到ITU-T G.722.1编解码器时,音频质量优于同码率下的G.722.1C编解码器。

关键词: 音频编码, 频带扩展, 音频分类, 递归图, 定量递归分析

Abstract:

A bandwidth extension method based on audio classification was proposed.Time series of audio signals were classified into four types based on recurrence plot and recurrence quantification analysis,and the fine spectrums were recovered by taking advantage of four methods respectively.In addition,the spectrum envelope and energy gain were adjusted by Gaussian mixture model and codebook mapping on the basis of soft decision respectively.Subjective and objective testing results indicate that the proposed method has good quality compared with conventional blind bandwidth extension methods,and the performance of ITU-T G.722.1 codec with the proposed algorithm is better than that of G.722.1C codec at the same bit rate.

Key words: audio coding, bandwidth extension, audio classification, recurrence plot, recurrence quantification analysis

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