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To some degree, artificially making the reconstructed spectra of audio signals temporally smooth is beneficial for the subjective quality and even can compensate some perceptual distortion caused by the error of the reconstructed spectra.
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4) Achieving the 'steady-state' spectrum of audio signals . Achieving the 'steady-state' spectrum of audio signals.
Figure 1 Example of phase trajectory for LF fine spectrum of audio signal.
Figure 2 Example of phase trajectory for HF fine spectrum of audio signal.
The spectral envelope was removed to obtain the fine spectrum of audio signals, and the phase space was reconstructed.
First, the ratio of the 'steady-state' spectrum to the smoothed spectrum of audio signals is determined for each channel at the current frame.
Then, the resulting 'steady-state' spectrum is further used to remove the transients from the original spectrum of audio signals by the spectral weighting method.
In the proposed method, the 'steady-state' spectrum of audio signals is first obtained by using MCRA for describing the spectrum components which are slowly evolved over time.
We found that for the MDCT spectrum of audio signals, a slight change of τ will lead to the adjacent phase points becoming completely uncorrelated.
The NMF, [21], where a matrix with positive values is decomposed into positive basis functions, has been applied for classification of TF spectrum of audio signals [22, 23].
As shown in Figure 5, the 'steady-state' spectrum of audio signals is able to describe the spectrum components which are slowly evolved over time, but the fine structure of audio spectrum is blurred.
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