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一种基于语音分类的清晰度客观评价算法
引用本文:张雄伟,沈刘平,曹铁勇,杨吉斌,孙新建. 一种基于语音分类的清晰度客观评价算法[J]. 解放军理工大学学报(自然科学版), 2007, 8(2): 103-107
作者姓名:张雄伟  沈刘平  曹铁勇  杨吉斌  孙新建
作者单位:解放军理工大学通信工程学院,江苏,南京210007;南京军区73061部队,江苏,徐州221121
摘    要:为了能方便、快捷、可靠地对失真语音进行语音清晰度性能评价,提出了一种基于语音分类的加权巴克谱失真语音清晰度客观评价算法SC-WBSD.该算法提出在巴克域中对清音帧、浊音帧及过渡音帧巴克带谱失真进行加权来求失真语音的客观失真测度.通过分析 3类语音的巴克谱失真测度与DRT分的相关程度,提出一组以相关系数的幂次方为权重的有效SC-WBSD权重矢量.实验结果表明,SC-WBSD方法和DRT分的相关度达到了0.924 73,与巴克谱失真测度算法相比提高了4%.

关 键 词:语音清晰度  客观评价  语音分类  加权巴克谱失真  相关度
文章编号:1009-3443(2007)02-0103-05
收稿时间:2006-04-12
修稿时间:2006-04-12

Objective speech articulation evaluation algorithm using weightedBark spectral distortion based on speech classification
ZHANG Xiong-wei,SHEN Liu-ping,CAO Tie-yong,YANG Ji-bin and SUN Xin-jian. Objective speech articulation evaluation algorithm using weightedBark spectral distortion based on speech classification[J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2007, 8(2): 103-107
Authors:ZHANG Xiong-wei  SHEN Liu-ping  CAO Tie-yong  YANG Ji-bin  SUN Xin-jian
Affiliation:Institute of Communications Engineering,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Institute of Communications Engineering,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Institute of Communications Engineering,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Institute of Communications Engineering,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Unit 73061,Nanjing Military Area Command,Xuzhou 221121,China
Abstract:A new objective articulation evaluation method SC-WBSD(weighted Bark spectral distortion based on speech classification) was presented.The calculation of objective distortion measurement based on speech classification was proposed.Through the analysis of correlation between three speech classes Bark band distortion used in BSD and DRT,an effective Bark spectral distortion weight vector based on power of each class band correlation coefficients was presented.Experimental result shows that the correlation between SC-WBSD and DRT has arrived at 0.92473.Compared with the BSD,SC-WBSD has a 4 percent increase in the correlation with DRT.
Keywords:measurment speech articulation   speech classification   weighted Bark spectral distortion   correlation coefficient
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