搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

水下噪声音色属性回归模型及其在目标识别中的应用

王娜 陈克安

引用本文:
Citation:

水下噪声音色属性回归模型及其在目标识别中的应用

王娜, 陈克安

Regression model of timbre attribute for underwater noise and its application to target recognition

Wang Na, Chen Ke-An
PDF
导出引用
  • 通过对声音的主观评价与客观分析而建立的主观感受数学模型,在许多领域都有重要的应用. 本文采用多元线性回归分析手段对水下噪声音色属性建立回归模型,提取音色特征并改善水下目标的识别效果. 首先,在前期水下噪声音色属性主观评价实验的基础上,将构成音色属性空间的5个成分的评价分值作为回归分析中的因变量,提取大量与听觉感知相关的听觉特征作为自变量;然后,通过相关分析和改进的逐步筛选法,挑选出反映音色属性的“最优”自变量子集;最后,利用向后剔除回归分析和水下目标识别实验,确定适当的音色模型,并通过假设检验证明该线性模型不仅正确有效,而且能改善水下目标识别效果.
    Timbre attribute is the most important feature to recognize a target. This paper presents a model of timbre features by multiple regression analysis applied in the recognition of underwater noise. At first, timbre attribute as a dependent variable is analyzed by the semantic differential evaluation and principal component analysis. And then an extended stepwise variables selection is proposed to select the optimal set as independent variables from auditory features that have been discussed in previous researches. Finally, the timbre features extracted by the regression model are used to recognize the underwater target. The results show that the extended regression analysis as a statistical method can find the relationship between timbre attribute and the auditory features. And the modeling timbre features calculated by several statistics of the sub-spectral features and the sub-temporal features are more effective than other features.
    • 基金项目: 西北工业大学基础研究基金(批准号:W018104)资助的课题.
    [1]

    [1]Zhou L W 2004 Targets Detection and Recognition (Beijing: Beijing Institute of Technology Press) (in Chinese) [周立伟 2004 目标探测与识别(北京:北京理工大学出版社)]

    [2]

    [2]Cai Y B, Zhang M Z, Shi X Z, Lin L J 1999 Acta Electron. Sin. 27 129 (in Chinese)[蔡悦斌、张明之、史习智、林良骥 1999 电子学报 27 129]

    [3]

    [3]Fan Y Y, Sun J C, Li P A, Xu J D, Shang J H 1999 Acta Acostica 24 611 (in Chinese)[樊养余、孙进才、李平安、许家栋、尚久浩 1999 声学学报 24 611]

    [4]

    [4]Collier G L 2004 Speech Commun. 43 297

    [5]

    [5]Zwicker H E, Fastl H 1999 Psychoacoustics: Facts and Models (Berlin Heidelberg: Springer-Verlag Press)

    [6]

    [6]Park T H 2004 Ph. D. Dissertation (Princeton : Princeton University)

    [7]

    [7]Wang N 2006 M. S. Thesis (Xi’an: Northwestern Polytechnical University) (in Chinese) [王娜 2006 硕士学位论文 (西安:西北工业大学)]

    [8]

    [8]Houtsma A J M 1997 J. New Music Res. 26 104

    [9]

    [9]Chen K A, Wang N, Wang J C 2009 Acta Phys. Sin. 58 5075 (in Chinese) [陈克安、王娜、王金昌 2009 物理学报 58 5075]

    [10]

    ]Grey J M 1977 J. Acoust. Soc. Am. 61 1270

    [11]

    ]Daniel J F 1990 J. Acoust. Soc. Am. 87 311

    [12]

    ]Mcadams S, Winsberg S, Donnadieu S, Soete G D, Krimphoff J 1995 Psychol. Res.58 177

    [13]

    ]Caclin A, McAdams S, Smith B K, Winsberg S 2005 J. Acoust. Soc. Am. 118 471

    [14]

    ]Agostini G, Longari M, Pollastri E 2003 Eu. Assoc. Sign. Proc.: J. Appl. Signal Proc. 1 5

    [15]

    ]Jensen K 1999 Ph. D. Dissertation (Copenhagen: University of Copenhagen)

    [16]

    ]Aucouturier J J, Pachet F, Sandler M 2005 IEEE Trans. Multimed. 7 1028

    [17]

    ]Burred J J 2008 Ph. D. Dissertation (Berlin: Technical University Berlin)

    [18]

    ]Chen K A, Ma M, Zhang Y N, Wang N, Yan L 2008 Acta Acostica 33 348 (in Chinese) [陈克安、马苗、张燕妮、王娜、闫靓 2008 声学学报 33 348]

    [19]

    ]Wang N, Chen K A, Huang H 2009 Acta Phys. Sin. 58 5730 (in Chinese) [王娜、陈克安、黄凰 2009 物理学报 58 5730]

    [20]

    ]Victor W Y, Paul C H 2007 J. Acoust. Soc. Am. 122 1502

    [21]

    ]Eronen A, Klapuri A 2000 Proceeding of the IEEE International Conference on Acoustics, Speech and Signal Processing Istanbul, Turkey, June 5—9, 2000 p753

    [22]

    ]Zhang X, Zbigniew W R 2007 International Conference on Multimedia and Ubiquitous Engineering Seoul, Korea, April 26—28, 2007 p3

    [23]

    ]Tindate A, Kapur A, Fuinaga I 2004 International Computer Music Conference Miami, Florida, USA, November 1—6, 2004 p592

    [24]

    ]Toh A M, Togneri R, Nordholm S 2005 Proceedings of Postgraduate Electrical Engineering and Computing Symposium Perth, Australia, September 7—10, 2005 p22

    [25]

    ]Giannakis K 2001 Ph. D. Dissertation (Middlesex: Middlesex University)

    [26]

    ]Liu D, Lu L, Zhang H J 2003 Proceeding of International Symposium on Music Information Retrieval Baltimore, Maryland, USA, October 27—30, 2003 p81

    [27]

    ]Wang N, Chen K A 2009 J. Syst. Sim. 21 3128 (in Chinese)[王娜、陈克安 2009 系统仿真学报 21 3128]

    [28]

    ]Wang N, Chen K A 2009 Acta Armament. 30 144 (in Chinese)[王娜、陈克安 2009 兵工学报 30 144]

    [29]

    ]Gao H X 2005 Applied Multivariate Statistical Analysis (Beijing: Peking University Press) p105 (in Chinese) [高惠璇 2005 应用多元统计分析 (北京:北京大学出版社) 第105页]

  • [1]

    [1]Zhou L W 2004 Targets Detection and Recognition (Beijing: Beijing Institute of Technology Press) (in Chinese) [周立伟 2004 目标探测与识别(北京:北京理工大学出版社)]

    [2]

    [2]Cai Y B, Zhang M Z, Shi X Z, Lin L J 1999 Acta Electron. Sin. 27 129 (in Chinese)[蔡悦斌、张明之、史习智、林良骥 1999 电子学报 27 129]

    [3]

    [3]Fan Y Y, Sun J C, Li P A, Xu J D, Shang J H 1999 Acta Acostica 24 611 (in Chinese)[樊养余、孙进才、李平安、许家栋、尚久浩 1999 声学学报 24 611]

    [4]

    [4]Collier G L 2004 Speech Commun. 43 297

    [5]

    [5]Zwicker H E, Fastl H 1999 Psychoacoustics: Facts and Models (Berlin Heidelberg: Springer-Verlag Press)

    [6]

    [6]Park T H 2004 Ph. D. Dissertation (Princeton : Princeton University)

    [7]

    [7]Wang N 2006 M. S. Thesis (Xi’an: Northwestern Polytechnical University) (in Chinese) [王娜 2006 硕士学位论文 (西安:西北工业大学)]

    [8]

    [8]Houtsma A J M 1997 J. New Music Res. 26 104

    [9]

    [9]Chen K A, Wang N, Wang J C 2009 Acta Phys. Sin. 58 5075 (in Chinese) [陈克安、王娜、王金昌 2009 物理学报 58 5075]

    [10]

    ]Grey J M 1977 J. Acoust. Soc. Am. 61 1270

    [11]

    ]Daniel J F 1990 J. Acoust. Soc. Am. 87 311

    [12]

    ]Mcadams S, Winsberg S, Donnadieu S, Soete G D, Krimphoff J 1995 Psychol. Res.58 177

    [13]

    ]Caclin A, McAdams S, Smith B K, Winsberg S 2005 J. Acoust. Soc. Am. 118 471

    [14]

    ]Agostini G, Longari M, Pollastri E 2003 Eu. Assoc. Sign. Proc.: J. Appl. Signal Proc. 1 5

    [15]

    ]Jensen K 1999 Ph. D. Dissertation (Copenhagen: University of Copenhagen)

    [16]

    ]Aucouturier J J, Pachet F, Sandler M 2005 IEEE Trans. Multimed. 7 1028

    [17]

    ]Burred J J 2008 Ph. D. Dissertation (Berlin: Technical University Berlin)

    [18]

    ]Chen K A, Ma M, Zhang Y N, Wang N, Yan L 2008 Acta Acostica 33 348 (in Chinese) [陈克安、马苗、张燕妮、王娜、闫靓 2008 声学学报 33 348]

    [19]

    ]Wang N, Chen K A, Huang H 2009 Acta Phys. Sin. 58 5730 (in Chinese) [王娜、陈克安、黄凰 2009 物理学报 58 5730]

    [20]

    ]Victor W Y, Paul C H 2007 J. Acoust. Soc. Am. 122 1502

    [21]

    ]Eronen A, Klapuri A 2000 Proceeding of the IEEE International Conference on Acoustics, Speech and Signal Processing Istanbul, Turkey, June 5—9, 2000 p753

    [22]

    ]Zhang X, Zbigniew W R 2007 International Conference on Multimedia and Ubiquitous Engineering Seoul, Korea, April 26—28, 2007 p3

    [23]

    ]Tindate A, Kapur A, Fuinaga I 2004 International Computer Music Conference Miami, Florida, USA, November 1—6, 2004 p592

    [24]

    ]Toh A M, Togneri R, Nordholm S 2005 Proceedings of Postgraduate Electrical Engineering and Computing Symposium Perth, Australia, September 7—10, 2005 p22

    [25]

    ]Giannakis K 2001 Ph. D. Dissertation (Middlesex: Middlesex University)

    [26]

    ]Liu D, Lu L, Zhang H J 2003 Proceeding of International Symposium on Music Information Retrieval Baltimore, Maryland, USA, October 27—30, 2003 p81

    [27]

    ]Wang N, Chen K A 2009 J. Syst. Sim. 21 3128 (in Chinese)[王娜、陈克安 2009 系统仿真学报 21 3128]

    [28]

    ]Wang N, Chen K A 2009 Acta Armament. 30 144 (in Chinese)[王娜、陈克安 2009 兵工学报 30 144]

    [29]

    ]Gao H X 2005 Applied Multivariate Statistical Analysis (Beijing: Peking University Press) p105 (in Chinese) [高惠璇 2005 应用多元统计分析 (北京:北京大学出版社) 第105页]

  • [1] 单明广, 刘翔宇, 庞成, 钟志, 于蕾, 刘彬, 刘磊. 结合线性回归的离轴数字全息去载波相位恢复算法. 物理学报, 2022, 71(4): 044202. doi: 10.7498/aps.71.20211509
    [2] 刘圣龙, 杨璐, 朱程君, 刘凯, 韩伟, 姚佳烽. 基于生物阻抗谱的细胞悬浮液浓度识别方法研究. 物理学报, 2022, 71(7): 078701. doi: 10.7498/aps.71.20211837
    [3] 单明广, 刘翔宇, 庞成, 钟志, 于蕾, 刘彬, 刘磊. 结合线性回归的离轴数字全息去载波相位恢复算法. 物理学报, 2021, (): . doi: 10.7498/aps.70.20211509
    [4] 卞晓鸽, 周胜, 张磊, 何天博, 李劲松. 基于标准样品回归算法和腔增强光谱的NO2检测方法. 物理学报, 2021, 70(5): 050702. doi: 10.7498/aps.70.20201322
    [5] 姚军财, 申静. 基于图像内容对比感知的图像质量客观评价. 物理学报, 2020, 69(14): 148702. doi: 10.7498/aps.69.20200335
    [6] 姚军财, 刘贵忠. 基于图像内容视觉感知的图像质量客观评价方法. 物理学报, 2018, 67(10): 108702. doi: 10.7498/aps.67.20180168
    [7] 苑博, 税国双, 汪越胜. 循环温度疲劳作用下粘接界面损伤的非线性超声评价. 物理学报, 2018, 67(7): 074302. doi: 10.7498/aps.67.20172265
    [8] 李家琨, 王霞, 金伟其, 张旭. 最小可分辨气体浓度的等效测试评价方法. 物理学报, 2015, 64(16): 160701. doi: 10.7498/aps.64.160701
    [9] 陈添兵, 姚明印, 刘木华, 林永增, 黎文兵, 郑美兰, 周华茂. 基于多元定标法的脐橙Pb元素激光诱导击穿光谱定量分析. 物理学报, 2014, 63(10): 104213. doi: 10.7498/aps.63.104213
    [10] 孟庆芳, 陈月辉, 冯志全, 王枫林, 陈珊珊. 基于局域相关向量机回归模型的小尺度网络流量的非线性预测. 物理学报, 2013, 62(15): 150509. doi: 10.7498/aps.62.150509
    [11] 杨立学, 陈克安, 伍莹. 基于听觉中枢模型的水下噪声音色表达与特性分析. 物理学报, 2013, 62(19): 194302. doi: 10.7498/aps.62.194302
    [12] 闫靓, 陈克安, Ruedi Stoop. 主观评价实验中声音样本剂量值的度量方法. 物理学报, 2013, 62(12): 124302. doi: 10.7498/aps.62.124302
    [13] 吕天阳, 谢文艳, 郑纬民, 朴秀峰. 加权复杂网络社团的评价指标及其发现算法分析. 物理学报, 2012, 61(21): 210511. doi: 10.7498/aps.61.210511
    [14] 周漩, 张凤鸣, 李克武, 惠晓滨, 吴虎胜. 利用重要度评价矩阵确定复杂网络关键节点. 物理学报, 2012, 61(5): 050201. doi: 10.7498/aps.61.050201
    [15] 闫靓, 陈克安, Ruedi Stoop. 多噪声源共同作用下的总烦恼度评价与预测. 物理学报, 2012, 61(16): 164301. doi: 10.7498/aps.61.164301
    [16] 王娜, 陈克安, 黄凰. 水下噪声听觉属性的主观评价与分析. 物理学报, 2009, 58(10): 7330-7338. doi: 10.7498/aps.58.7330
    [17] 欧阳敏, 费 奇, 余明晖. 基于复杂网络的灾害蔓延模型评价及改进. 物理学报, 2008, 57(11): 6763-6770. doi: 10.7498/aps.57.6763
    [18] 沈自才, 沈 建, 刘世杰, 孔伟金, 邵建达, 范正修. 渐变折射率薄膜的分层评价探讨. 物理学报, 2007, 56(3): 1325-1328. doi: 10.7498/aps.56.1325
    [19] 袁坚, 肖先赐. 观测窗中多元非线性时间序列的分析. 物理学报, 1997, 46(11): 2095-2103. doi: 10.7498/aps.46.2095
    [20] 包紫薇, 魏荣爵. 用语噪声法研究发音人的音色特征. 物理学报, 1978, 27(4): 476-479. doi: 10.7498/aps.27.476
计量
  • 文章访问数:  6368
  • PDF下载量:  1120
  • 被引次数: 0
出版历程
  • 收稿日期:  2009-07-30
  • 修回日期:  2009-08-18
  • 刊出日期:  2010-02-05

水下噪声音色属性回归模型及其在目标识别中的应用

  • 1. 西北工业大学环境工程系,西安 710072
    基金项目: 西北工业大学基础研究基金(批准号:W018104)资助的课题.

摘要: 通过对声音的主观评价与客观分析而建立的主观感受数学模型,在许多领域都有重要的应用. 本文采用多元线性回归分析手段对水下噪声音色属性建立回归模型,提取音色特征并改善水下目标的识别效果. 首先,在前期水下噪声音色属性主观评价实验的基础上,将构成音色属性空间的5个成分的评价分值作为回归分析中的因变量,提取大量与听觉感知相关的听觉特征作为自变量;然后,通过相关分析和改进的逐步筛选法,挑选出反映音色属性的“最优”自变量子集;最后,利用向后剔除回归分析和水下目标识别实验,确定适当的音色模型,并通过假设检验证明该线性模型不仅正确有效,而且能改善水下目标识别效果.

English Abstract

参考文献 (29)

目录

    /

    返回文章
    返回