NDLI: Speech-stream detection with low signal-to-noise ratios based on empirical mode decomposition and fourth-order statistics

Content Provider	IEEE Xplore Digital Library
Author	Xueyao Li Wu Wang Rubo Zhang
Copyright Year	2007
Description	Author affiliation: Harbin Eng. Univ., Harbin (Xueyao Li)
Abstract	Speech-stream detection plays an important role in short-wave communication. It is tiring for a person to listen something for a long time, especially in adverse environments. An algorithm for speech-stream detection in noisy environments, based on the empirical mode decomposition (EMD) and the statistical properties of higher-order cumulants of speech signals is presented. 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. Besides that, with the self-adaptive decomposition by the 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 SNR, and the algorithm is robust in the real signal tests.
Starting Page	187
Ending Page	191
File Size	273803
Page Count	5
File Format	PDF
ISBN	9780769530390
DOI	10.1109/IMSCCS.2007.93
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech coding Gaussian noise Working environment noise Signal processing algorithms Speech enhancement Signal processing Frequency Statistics Signal analysis Signal to noise ratio
Content Type	Text
Resource Type	Article

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