Maximum Entropy Spectral Analysis of Hoarse Voices.

Maximum entropy spectral analysis

A review of the maximum entropy spectral analysis (MESA) method for time series is presented. Then, empirical evidence based on maximum entropy spectra of real seismic data is shown to suggest that M = 2N/ ln 2N is a reasonable a priori choice of the operator length M for discrete time series of length N . Various data examples support this conclusion.

Synthetic hoarse voices: a perceptual evaluation

Pitch and noise estimation in hoarse voices

In pathologic voices, both slow and fast pitch variations within an utterance are indicative of the patient status. Moreover, the spectrogram of such voices usually shows high noise components, closely related to the degree of perceived hoarseness of the voice. In the present paper, both pitch and noise variations are tracked during an utterance. This is accomplished by means of a two-step proc...

Spectral moment matching in the maximum entropy spectral analysis method

The formula for the spectral moments is expanded in a series consisting of autocorrelation terms. By using the autocorrelation extrapolation inherent in the maximum entropy method (MEM) for spectral analysis, it is found that good estimates of the moments can be found from a very low order autoregressive model. The motivation for this investigation came from results obtained during spectral ana...

Maximum Entropy and Spectral Estimation

The temperature of a gas corresponds to the average kinetic energy of the molecules in the gas. What can we say about the distribution of velocities in the gas at a given temperature? We know from physics that this distribution is the maximum entropy distribution under the temperature constraint, otherwise known as the Maxwell-Boltzmann distribution. The maximum entropy distribution corresponds...