Application of model order reduction approach on quality evaluation of speech signal

In this paper, a model order reduction approach has been used to compare the performance of hearing quality of the voice sound of lower and higher order systems. To implement this, an input signal in the form of one of the standard speech signal from IPA database has been applied on the original higher order system as well as on the reduced order system. This form of the input signal is applied to generate the voice sound of the speech signal and a comparison is being made on the hearing quality of the output of both the systems. First of all, one of the model reduction approach i.e. Schur approach has been applied on the original higher order system to obtain a reduced order system by eliminating undesired order without losing any key properties of original higher order system. Now, the reduced order system contains the lower order as desired by the user. After that, an input speech signal is applied separately on both the systems. Then, the outputs of both the systems have been obtained by the convolution operation. Further, the output signal of original higher order system in distorted form and reconstructed signal of the lower order system are obtained by de-convolution operation separately. Finally, a comparison has been made on the output signals of both the systems and observed that the voice sound of generated speech signal by lower order system has good hearing quality. But the generated voice sound by original higher order system has lost its quality. So, a model order reduction approach gives far much better hearing quality of the voice sound by the processing through lower order system in comparison with the original higher order system.

[1]  G.D. Cain,et al.  Approximation of FIR by IIR digital filters: an algorithm based on balanced model reduction , 1992, IEEE Trans. Signal Process..

[2]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[3]  Carolyn L. Beck,et al.  MRedTool - a MATLAB toolbox for model reduction of multi-dimensional systems , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[4]  Arun Kumar,et al.  Two-scale Auditory Feature Based Non-intrusive Speech Quality Evaluation , 2010 .

[5]  Khalid Sayood,et al.  Introduction to Data Compression , 1996 .

[6]  Daoud Berkani,et al.  Low-order model for speech signals , 2004, Signal Processing.

[7]  B. Siddik Yarman,et al.  A novel method to represent speech signals , 2005, Signal Process..

[8]  Cornel Ioana,et al.  Polynomial phase signal modeling using warping-based order reduction , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Thomas Quatieri,et al.  Discrete-Time Speech Signal Processing: Principles and Practice , 2001 .

[10]  Lahcène Mitiche,et al.  Speech Modeling via Model Reduction , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[11]  B. Siddik Yarman,et al.  A New Method to Represent Speech Signals Via Predefined Signature and Envelope Sequences , 2007, EURASIP J. Adv. Signal Process..

[12]  Lahcène Mitiche,et al.  Speech modelling by model-order reduction: SNR behaviour , 2003 .

[13]  M. Lobur,et al.  The criteria of compression quality evaluation , 2004, Proceedings of the International Conference Modern Problems of Radio Engineering, Telecommunications and Computer Science, 2004..

[14]  Lihua Xie,et al.  A new technique to filter reduction for speech signal processing systems , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[15]  L. Mitiche,et al.  A new approach for speech modeling based on model reduction , 2004, First International Symposium on Control, Communications and Signal Processing, 2004..

[16]  A. Laub,et al.  Computation of system balancing transformations and other applications of simultaneous diagonalization algorithms , 1987 .

[17]  Magda Osman,et al.  Control Systems Engineering , 2010 .

[18]  Q. Naeem,et al.  Improving audio data quality and compression , 2008, 2008 4th International Conference on Emerging Technologies.

[19]  Lahcène Mitiche,et al.  Comparative study of model reduction schemes - application to the digital filters synthesis , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).

[20]  Bo Wahlberg ARMA spectral estimation of narrow-band processes via model reduction , 1990, IEEE Trans. Acoust. Speech Signal Process..

[21]  M.G. Bellanger,et al.  Digital processing of speech signals , 1980, Proceedings of the IEEE.

[22]  Vimal Singh,et al.  Control Systems Engineering , 1976, IEEE Transactions on Systems, Man, and Cybernetics.