Title :
Frequency weighted linear prediction
Author :
Chu, Peter L. ; Messerschmitt, D.
Author_Institution :
University of California, Berkeley, California
Abstract :
A new spectral distance measure is defined by inserting a multiplicative frequency weighting term into the conventional Itakura-Saito measure. Then the weighting function is a simple one pole function, then the minimization of the distance between a signal spectrum and an arbitrary N-pole filter results in a set of linear equations that is symmetric and solvable by Cholesky decomposition. When the weighting function is a multiple pole function, the resulting spectral distance minimization produces a set of nonlinear algebraic equations, but fortunately a simple method exists for obtaining an approximate solution which can be refined using the Newton- Raphson method. Results of some preliminary trials in applying the technique to LPC vocoding are described.
Keywords :
Autocorrelation; Filters; Fourier transforms; Frequency estimation; Frequency measurement; Gain measurement; Linear predictive coding; Nonlinear equations; Speech; Weight measurement;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '82.
DOI :
10.1109/ICASSP.1982.1171527