文章摘要
陈晓梅,王晓玮,钟波,商莹莹,杨佳燕.采用双谱特征的语音可懂度评价算法[J].声学技术,2022,41(5):678~684
采用双谱特征的语音可懂度评价算法
Speech intelligibility evaluation algorithm using bispectral features
投稿时间:2021-01-12  修订日期:2021-04-11
DOI:10.16300/j.cnki.1000-3630.2022.05.007
中文关键词: 语音可懂度  客观评价算法  高阶统计  双谱
英文关键词: speech intelligibility  objective evaluation algorithm  high-order statistics  bispectrum
基金项目:国家重点研发计划“主动健康和老龄化科技应对”专项(2020YFC2005200)课题
作者单位E-mail
陈晓梅 华北电力大学电气与电子工程学院, 北京 102206  
王晓玮 华北电力大学电气与电子工程学院, 北京 102206  
钟波 中国计量科学研究院力学与声学计量科学研究所, 北京 100029 lilun1980@126.com 
商莹莹 中国医学科学院北京协和医院耳鼻喉科, 北京 100730  
杨佳燕 中国医学科学院北京协和医院耳鼻喉科, 北京 100730  
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中文摘要:
      针对现有的语音可懂度评价方法不能有效地处理信号在多种类型的非线性失真下的变化,提出了一种基于双谱特征的语音可懂度评价(Bispectral Speech Intelligibility Metric,BSIM)算法,用三阶统计量从语音信号的谱图中提取特征。双谱可以检测语音信号中的非线性相位耦合,抑制非高斯信号中的高斯噪声,从而揭示更多隐含于信号内部的有用信息。将本方法与现有的语音可懂度指标进行了比较,结果表明,此方法可以成功地预测线性失真和非线性失真造成的语音可懂度下降,其评价结果与主观可懂度结果具有很高的相关度,对信号失真变化敏感。
英文摘要:
      Aiming at the fact that the existing speech intelligibility evaluation methods cannot effectively deal with the signal changes under various types of nonlinear distortions, a bispectral speech intelligibility metric (BSIM) algorithm based on bispectral features is proposed, which uses third-order statistics to extract features from the spectrogram of speech signal. Bispectrum can detect the nonlinear phase coupling in the speech signal and suppress the Gussian noise in the non-Gussian signal, thereby can reveal more useful information hidden in the signal. This method is compared with existing speech intelligibility indicators. The results show that this method can successfully predict the degradation of speech intelligibility caused by linear distortion and nonlinear distortion. The evaluation result is highly correlated with the subjective intelligibility result and sensitive to signal distortion changes.
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