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Novel speech spectra all-pole modelling based upon selective even-samples linear prediction
Chang K.F.; Cheong P.; Ting S.W.; Tarn K.W.
2000-12-01
Conference Name7th IEEE International Conference on Electronics, Circuits and Systems
Source PublicationICECS 2000: 7TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS & SYSTEMS, VOLS I AND II
Volume2
Pages1022-1025
Conference DateDEC 17-19, 2000
Conference PlaceJOUNIEH, LEBANON
Abstract

In this paper, a novel linear predictive method (SELP) for speech spectra modelling is proposed. This method allows 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. 

DOI10.1109/ICECS.2000.913049
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000167666700238
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Chang K.F.,Cheong P.,Ting S.W.,et al. Novel speech spectra all-pole modelling based upon selective even-samples linear prediction[C],2000:1022-1025.
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