Advanced Search
Volume 23 Issue 10
Oct.  2001
Turn off MathJax
Article Contents
Lichao YANG, Mengdao XING, Guangcai SUN, Anle WANG, Jialian SHENG. A Novel ISAR Imaging Algorithm for Microwave Photonics Radar[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1271-1279. doi: 10.11999/JEIT180661
Citation: Wu Qihui, Wang Jinlong. VOICE DETECTION BASED ON SPECTRAL ENTROPY[J]. Journal of Electronics & Information Technology, 2001, 23(10): 989-993.

VOICE DETECTION BASED ON SPECTRAL ENTROPY

  • Received Date: 1999-10-19
  • Rev Recd Date: 2000-04-07
  • Publish Date: 2001-10-19
  • An approach is introduced to voice detection that differs from normal approach via energy, correlation and zerocrossing criteria. By measuring the gross shape of the short-term speech spectrum using spectral entropy to detect voice segment, it is shown that the spectral entropy can be used effectively even in heavy background noise. The simulation results show that the approach via spectral entropy has good performance for anti-noice.
  • F. Beritelli, S. Casale, A. Cavallaro, A robust voice activity detector for wireless communications using soft computing, IEEE J. on SAC, 1998, SAC-16(9), 1818-1829.[2]R.V. Cox, P. Kroon, Low bit-rate speech coders for multimedia communication, IEEE Commun.Mag., 1996, 34(1), 34-41.[3]Qualcomm, Inc., Digital Cellular System CDMA Analog Dual-Mode Mobile Station-Base Station Compatibility Standard, March 5, 1992.[4]L.R. Rabiner, On the use of autocorrelation analysis for pitch detection, IEEE Trans. on Acoust.,Speech, Signal Processing, 1977, ASSP-25(1), 24-33.[5]S. Seneff, Real-time harmonic pitch detector, IEEE Trans. on Acoust, Speech, Signal Processing,1978, ASSP-26(2), 358-365.[6]A. Bendiksen.[J].K. Steiglitz, Neural networks for voiced/unvoiced speech classification, ICASSP90.,Bonn, Germany.1990,:-[7]高文,多媒体数据压缩技术,北京:电子工业出版社,1992,48[8]Byeong Gi Lee, A new algorithm to compute the discrete cosine transform, IEEE Trans. on Acoust., Speech, Signal Processing, 1984, ASSP-32(6), 1243-1245.[9]N. Ahmed, T. Natarajan, K. R. Rao, Discrete cosine transform, IEEE Trans. on Computer, 1974,C-23(1), 90-93.[10]傅祖芸,信息论基础,北京:电子工业出版社,1989年,23.
  • Cited by

    Periodical cited type(10)

    1. 高永胜,谭佳俊,王瑞琼. 基于光子学的微波移频方法研究. 电子与信息学报. 2023(06): 2123-2133 . 本站查看
    2. 陈学斌,叶春茂,张彦,胡庆荣. 含旋转部件的ISAR目标分离式成像. 信号处理. 2021(02): 209-221 .
    3. 杨磊,夏亚波,毛欣瑶,廖仙华,方澄,高洁. 基于分层贝叶斯Lasso的稀疏ISAR成像算法. 电子与信息学报. 2021(03): 623-631 . 本站查看
    4. 谢意远,高悦欣,邢孟道,郭亮,孙光才. 跨谱段SAR散射中心多维参数解耦和估计方法. 电子与信息学报. 2021(03): 632-639 . 本站查看
    5. 范北辰,杨悦,马丛,王祥传,张方正,潘时龙. 微波光子雷达组网技术. 雷达科学与技术. 2021(02): 195-207+216 .
    6. 王安乐,王党卫,余岚. 微波光子成像雷达技术发展综述. 雷达科学与技术. 2021(02): 217-224+232 .
    7. 侯颖妮,谢洁. 稀疏采样数据大转角高分辨ISAR成像技术研究. 雷达科学与技术. 2021(05): 604-609+624 .
    8. 赵忠凯,陈通. ISAR基带干扰系统设计与实现. 应用科技. 2020(03): 24-29 .
    9. 俞传龙. 逆合成孔径雷达成像算法的研究与仿真. 电子设计工程. 2020(23): 183-187 .
    10. 熊强强,陈黎艳,姚卫国,曾美琳. 可调光子滤波器微波信号接收码元速率估计. 激光杂志. 2020(12): 181-184 .

    Other cited types(9)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (2112) PDF downloads(523) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return