NDLI: Novel speech spectra all-pole modelling based upon selective even-samples linear prediction

Content Provider	IEEE Xplore Digital Library
Author	Chang, K.F. Cheong, P. Ting, S.W. Tam, K.W.
Copyright Year	2000
Description	Author affiliation: Fac. of Sci. & Technol., Macau Univ., China (Chang, K.F.)
Abstract	In this paper, a novel linear predictive method (SELP) for speech spectra modelling is proposed. This method allows one to develop an all-pole filter which combines p+1 consecutive even preceding samples of the speech signal x(n) into p pairs for linear extrapolation. In addition, a weighting selective scheme is employed to obtain high signal-to-error ratio (SER). Comparing to the traditional LPC modelling, the proposed filter's order is then raised to 2p+2 when both filters are with p-normal equations. In order to demonstrate the proposed method usefulness, this new model is simulated at 22.05 kHz speech spectra. Experimental results show that at least 10 dB SER improvement is obtained with p=5 when compared with that of LPC modelling.
Starting Page	1022
Ending Page	1025
File Size	356432
Page Count	4
File Format	PDF
ISBN	0780365429
DOI	10.1109/ICECS.2000.913049
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-12-17
Publisher Place	Lebanon
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Linear predictive coding Extrapolation Frequency conversion Nonlinear filters Equations Speech recognition Spectral analysis Information rates Bit rate
Content Type	Text
Resource Type	Article

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