Sentence examples for coefficients of speech from inspiring English sources

According to [15], the DFT coefficients of speech and noise can be seen as asymptotically independent Gaussian random variables.

The variance is equal to the power of a signal because the DFT coefficients of speech signal and noise signal are modeled as zero-mean complex Gaussian variables.

Y(ω k ), X(ω k ), and D(ω k ) denote the kth DFT coefficients of noisy speech, clean speech, and noise signal, respectively.

To solve the equations required for threshold determination, the TE-operated WP coefficients of noisy speech, clean speech, or noise is well approximated by the positive part of a Gaussian distribution.

Some speech enhancement methods [1, 4 7] are often operated in the discrete Fourier transform (DFT) domain, that is, the enhanced speech is obtained by estimating DFT coefficients of clean speech from the noisy speech.

In this paper, a new thresholding-based speech enhancement approach, where the threshold is statistically determined using the Teager energy-operated wavelet packet (WP) coefficients of noisy speech, is proposed.

Figure 3 Probability distribution of TE-operated WP coefficients of noisy speech.

Figure 2 Probability distribution of TE-operated WP coefficients of clean speech.

where λ s,k and λ n,k are the variances of MP coefficients of clean speech and noise, respectively.

where α s,k and α n,k are the MP coefficients of clean speech and noise, respectively.

In this article, we assume that the MP coefficients of noisy speech and noise signal are asymptotically independent complex Gaussian random variables with zero means.