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语音信号传输过程中的阈上随机共振现象

Suprathreshold Stochastic Resonance in Speech Signal Transmission
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摘要 对利用阈上随机共振现象来改善语音信号的传输进行了研究。在理论上,选取输入输出互相关系数作为测度,用拉普拉斯信号模拟语音信号,研究了拉普拉斯信号在多阈值系统中受到加性高斯噪声和乘性高斯噪声作用下的阈上随机共振现象。在实际应用中,同样选取输入输出互相关系数作为测度,用真实的语音信号作为输入信号,在受到加性高斯噪声和乘性高斯噪声共同作用下的多阈值系统中进行仿真。理论研究结果表明,在受加性噪声和乘性噪声共同作用情况下的多阈值系统中,当噪声强度在一定范围内变化时,该系统中出现了阈上随机共振现象。仿真结果表明,语音信号在上述系统中传输时,也发生了阈上随机共振现象,即验证了利用阈上随机共振可以改善语音信号的传输。 The use of suprathreshold stochastic resonance to improve speech signals transmission is studied.In theory,the suprathreshold stochastic resonance phenomenon of Laplace signals under the action of additive Gaussian noise and multiplicative Gaussian noise in multithreshold system is studied by using Laplace signals to simulate speech signals by taking the correlation coefficient of input and output as a measure.In practical application,the input-output correlation coefficient is also selected as the measure,and the real speech signals are used as the input signal to simulate in a multithreshold system under the combined action of additive Gaussian noise and multiplicative Gaussian noise.The theoretical results show that suprathreshold stochastic resonance occurs when the noise intensity changes within a certain range in a multithreshold system under the combined action of additive and multiplicative noises.The simulation results show that suprathreshold stochastic resonance also occurs when the speech signals are transmitted in the above system,that is,it is verified that suprathreshold stochastic resonance can improve the transmission of speech signals.
作者 王杰 王友国 翟其清 WANG Jie;WANG You-guo;ZHAI Qi-qing(School of Science,Nanjing University of Posts and Telecommunications,Nanjing 210046,China)
出处 《计算机技术与发展》 2021年第2期155-160,共6页 Computer Technology and Development
基金 国家自然科学基金(61771256) 通信与网络技术国家工程研究中心开放基金(GCZX001)。
关键词 阈上随机共振 语音传输 相关系数 拉普拉斯信号 多阈值系统 suprathreshold stochastic resonance speech signal transmission correlation coefficient Laplace signals multithreshold system
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  • 1张仲海,王多,王太勇,林锦州,蒋永翔.采用粒子群算法的自适应变步长随机共振研究[J].振动与冲击,2013,32(19):125-130. 被引量:22
  • 2李建东,李明远,纪红.话音活动检测的模型及其在移动通信中的应用[J].电信科学,1995,11(10):22-25. 被引量:1
  • 3冷永刚,王太勇,郭焱,吴振勇.双稳随机共振参数特性的研究[J].物理学报,2007,56(1):30-35. 被引量:55
  • 4Ostendorf M, Favre B, Grishman R, et al.. Speech segmentation and spoken document processing[J]. IEEE Signal Processing Magazine, 2008, 25(3): 59-69.
  • 5Bouamrane M M and Luz S. Meeting browsing state-of-the- art review[J]. Multimedia Systems, 2007, 12(4-5): 439-457.
  • 6Tur G, Stolcke A, Voss L, et al.. The CALO meeting assistant system[J]. IEEE Transactions on Audio, Speech and Language Processing, 2010, 18(6): 1601-1611.
  • 7Margarita K, Vassiliki M, and Constantine K. Speaker segmentation and clustering[J]. Signal Processing, 2008, 88(5) 1091-1124.
  • 8Xavier A and Jean-Francois B. Fast speaker diarization based on binary keys[C]. International Conference on Acoustics, Speech and Signal Processing, IEEE, Prague, 2011: 4428-4431.
  • 9Imseng D and Friedland G. Tuning-robust initialization methods for speaker diarization[J]. IEEE Transactions on Audio, Speech and Language Processing, 2010, 18(8): 2028-2037.
  • 10Valente F, Motlicek P, and Vijayasenan D. Variational Bayesian speaker diarization of meeting recordings[C]. International Conference on Acoustics, Speech and Signal Processing, IEEE, Dallas, 2010: 4954-4957.

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