Fast Sequential LS Estimation for Sinusoidal Modeling and Decomposition of Audio Signals

This work demonstrates a sequential Least Squares algorithm applied to the decomposition of sounds into sines-plus-residual models. For a given basis of r distinct frequency components, the algorithm derives recursively the Least Squares estimates of the associated amplitudes and phases. While a direct calculation achieves a O(nr2) complexity the main cost of our implementation is only of 4r multiplications per sample, whatever the length n of the analysis window. The technique is extended to basis of exponentially increasing or decreasing frequency components, which provides a fast and enhanced decomposition of rapidly varying segments of the sound. Finally, the proposed method is successfully applied to a real piano note.

[1]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[2]  Jian Li,et al.  Amplitude estimation of sinusoidal signals: survey, new results, and an application , 2000, IEEE Trans. Signal Process..

[3]  Julius O. Smith,et al.  Spectral modeling synthesis: A sound analysis/synthesis based on a deterministic plus stochastic decomposition , 1990 .

[4]  D. Mehta,et al.  Synthesis, analysis, and pitch modification of the breathy vowel , 2005, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005..

[5]  Roland Badeau,et al.  Hrhatrac Algorithm for Spectral Line Tracking of Musical Signals , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[6]  Xavier Serra,et al.  A sound analysis/synthesis system based on a deterministic plus stochastic decomposition , 1990 .

[7]  Søren Holdt Jensen,et al.  On perceptual distortion minimization and nonlinear least-squares frequency estimation , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[8]  Julius O. Smith,et al.  AM/FM rate estimation for time-varying sinusoidal modeling , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[9]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[10]  Stephen Travis Pope,et al.  Musical Signal Processing , 1997 .

[11]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[12]  Udo Zoelzer,et al.  DAFX: Digital Audio Effects , 2011 .