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With the rapid development of remote sensing technology, our ability to obtain remote sensing data has been improved to an unprecedented level. We have entered an era of big data. Remote sensing data clear showing the characteristics of Big Data such as hyper spectral, high spatial resolution, and high time resolution, thus, resulting in a significant increase in the volume, variety, velocity and...
A new wavelet-based method is presented in this work for estimating and tracking the pitch period. The main idea of the proposed new approach consists in extracting the cepstrum excitation signal and applying on it a wavelet transform whose resulting approximation coefficients are smoothed, for a better pitch determination. Although the principle of the algorithms proposed has already been considered...
In this paper, we present a recent algorithm for pitch detection based on an implicit circular autocorrelation of the glottal excitation signal. This algorithm operates in real time without the use of any post-processing technique. This article focuses on the correction of the pitch contours estimated and on the reduction in classification errors in speech signals using simple voicing decision techniques...
In the current paper, we propose a new pitch tracking technique based on a wavelet transform in the temporal domain. Our algorithm is designed to determine the pitch frequency of the speech signal using a simple voicing decision algorithm. The pitch period is extracted from the cepstrum excitation signal processed by a wavelet transform; then the pitch contour is refined by thresholding and correction...
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