Amplitude modulated model for analyzing non-stationary speech signals

Abstract

Recently amplitude modulated (AM) model in presence of additive white noise was used to analyze certain non-stationary speech data. It is observed that the assumption of white noise may not be proper in many cases. In this article, we consider the AM signal model in presence of stationary noise. We consider the least squares estimators and the estimators obtained by maximizing the Periodogram function. The two estimators are asymptotically equivalent. We study the theoretical properties of both estimators and observe their performances through numerical simulations. One speech data is analyzed and it is observed that the performance of the proposed estimators is quite satisfactory.

Keywords:

• Strong consistency
• Frequencies
• Amplitudes
• Asymptotic distribution

Acknowledgements

The authors would like to thank Professor G.C. Ray of Department of Electrical Engineering, I.I.T. Kanpur for providing the speech data. The authors would also like to thank two referees for some very constructive suggestions and the editor Professor Dr. Olaf Bunke for encouragements.