Download Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation In this article the estimation of the spectral envelope of sound signals is addressed. The intended application for the developed algorithm is pitch shifting with preservation of the spectral envelope in the phase vocoder. As a first step the different existing envelope estimation algorithms are investigated and their specific properties discussed. As the most promising algorithm the cepstrum based iterative true envelope estimator is selected. By means of controlled sub-sampling of the log amplitude spectrum and by means of a simple step size control for the iterative algorithm the run time of the algorithm can be decreased by a factor of 2.5-11. As a remedy for the ringing effects in the the spectral envelope that are due to the rectangular filter used for spectral smoothing we propose the use of a Hamming window as smoothing filter. The resulting implementation of the algorithm has slightly increased computational complexity compared to the standard LPC algorithm but offers significantly improved control over the envelope characteristics. The application of the true envelope estimator in a pitch shifting application is investigated. The main problems for pitch shifting with envelope preservation in a phase vocoder are identified and a simple yet efficient remedy is proposed.
Download Adaptive Threshold Determination for Spectral Peak Classification A new approach to adaptive threshold selection for classification of peaks of audio spectra is presented. We here extend the previous work on classification of sinusoidal and noise peaks based on a set of spectral peak descriptors in a twofold way: on one hand we propose a compact sinusoidal model where all the modulation parameters are defined with respect to the analysis window. This fact is of great importance as we recall that the STFT spectra are closely related to the analysis window properties. On the other hand, we design a threshold selection algorithm that allows us to control the decision thresholds in an intuitive manner. The decision thresholds calculated from the relationships established between the noise power in the signal and the distributions of sinusoidal peaks assures that all peaks described as sinusoidal will be correctly classified. We also show that the threshold selection algorithm can be used for different types of analysis windows with only a slight parameter readjustment.
Download A Reduced Multiple Gabor Frame for Local Time Adaptation of the Spectrogram In this paper we propose a method for automatic local time adaptation of the spectrogram of an audio signal, based on its decomposition within a Gabor multi-frame. The sparsity of the analyses within each individual frame is evaluated through the Rényi entropies measures. According to the sparsity of the decompositions, an optimal resolution and a reduced multi-frame are determined, defining an adapted spectrogram with variable resolution and hop size. The composition of such a reduced multi-frame allows an immediate definition of a dual frame: re-synthesis techniques for this adapted analysis are easily derived by the traditional phase vocoder scheme.