【摘 要】
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To capture the presence of speech embedded in nonspeech events and background noise in shortwave non-cooperative communication,an algorithm for speech-stream de
【机 构】
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College of Computer Science and Technology
论文部分内容阅读
To capture the presence of speech embedded in nonspeech events and background noise in shortwave non-cooperative communication,an algorithm for speech-stream detection in noisy environments is presented based on Empirical Mode Decomposition (EMD) and statistical properties of higher-order cumulants of speech signals.With the EMD, the noise signals can be decomposed into different numbers of IMFs.Then,the fourth-order cumulant(FOC)can be used to extract the desired feature of statistical properties for IMF components.Since the higher-order cumulants are blind for Gaussian signals, the proposed method is especially effective regarding the problem of speech-stream detection,where the speech signal is distorted by Gaussian noise.With the self-adaptive decomposition by EMD,the proposed method can also work well for non-Gaussian noise.The experiments show that the proposed algorithm can suppress different noise types with different SNRs, and the algorithm is robust in real signal tests.
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