On noise reduction in the Karhunen-Loève expansion domain
نویسندگان
چکیده
In this paper, we study the noise-reduction problem in the KarhunenLoève expansion domain. We develop two classes of optimal filters. The first class estimates a frame of speech by filtering the corresponding frame of the noisy speech. We will show that several well-known existing methods belong or are closely related to this category. The second class, which has not been studied before, obtains noise reduction by filtering not only the current frame, but also a number of previous consecutive frames of the noisy speech. We will discuss how to design the optimal noise-reduction filters in each class and demonstrate the properties of the deduced optimal filters.
منابع مشابه
Study of the Noise-Reduction Problem in the Karhunen-LoÈve Expansion Domain
Noise reduction, which aims at estimating a clean speech from a noisy observation, has long been an active research area. The standard approach to this problem is to obtain the clean speech estimate by linearly filtering the noisy signal. The core issue, then, becomes how to design an optimal linear filter that can significantly suppress noise without introducing perceptually noticeable speech ...
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