A model order based sinusoid representation for audio signals

This work investigates the problem of sinusoidal parameter estimation including amplitude, frequency and phase in all kinds of audio signals including speech, music and mixtures using a nonlinear least-squares (NLS) estimator where the number of sinusoids is in general unknown. A solution to the sinusoid order selection problem is presented by employing the NLS method along with some information criteria (IC) such as minimum description length (MDL) or AIC. The simulation results demonstrate that the presented approach is successful in determining the number of sinusoids used in sinusoidal representation by using the information provided by well-known ICs'. It is demonstrated that the original audio signal can successfully be reconstructed in terms of both objective (SSNR) and subjective results (MOS).

[1]  Thomas F. Quatieri,et al.  Speech analysis/Synthesis based on a sinusoidal representation , 1986, IEEE Trans. Acoust. Speech Signal Process..

[2]  A. Sabharwal,et al.  Model order selection for summation models , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[3]  H. Akaike A new look at the statistical model identification , 1974 .

[4]  Sadaoki Furui,et al.  Advances in Speech Signal Processing , 1991 .

[5]  Mark A. Clements,et al.  Sinusoidal modeling and modification of unvoiced speech , 1997, IEEE Trans. Speech Audio Process..

[6]  J. Rissanen Estimation of structure by minimum description length , 1982 .

[7]  William A. Gardner Comments on "Convergence analysis of LMS filters with uncorrelated data" , 1986, IEEE Trans. Acoust. Speech Signal Process..

[8]  Douglas Lake,et al.  Efficient Maximum Likelihood Estimation for Multiple and Coupled Harmonics , 1999 .

[9]  Phillip A. Regalia,et al.  On the behavior of information theoretic criteria for model order selection , 2001, IEEE Trans. Signal Process..

[10]  A. Sayadiyan,et al.  A Fixed Dimension Modified Sinusoid Model (FD-MSM) for Single Microphone Sound Separation , 2007, 2007 IEEE International Conference on Signal Processing and Communications.

[11]  Arye Nehorai,et al.  Adaptive comb filtering for harmonic signal enhancement , 1986, IEEE Trans. Acoust. Speech Signal Process..