Subspectral modeling in filter banks

Author

Benyassine, Adil ; Akansu, Ali N.

Author_Institution

Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

43

Issue

12

fYear

1995

fDate

12/1/1995 12:00:00 AM

Firstpage

3050

Lastpage

3053

Abstract

The article deals with spectral modeling in filter banks. It is shown, both theoretically and experimentally, that subspectral modeling is superior to full spectrum modeling if performed before the rate change. The price paid for this performance improvement is an increase of computations. A few different signal sources were considered in this study. It is shown that the performance of AR and ARMA techniques are comparable in subspectral modeling. The first is desired because of its simplicity. As an application of this study, we implemented a CELP based speech codec embedded in a filter bank structure. We found that there were no performance improvements of subband CELP technique over the fullband case. The theoretical reasonings of the experimental results are also given

Keywords

autoregressive moving average processes; autoregressive processes; band-pass filters; filtering theory; linear predictive coding; spectral analysis; speech codecs; speech coding; AR techniques; ARMA techniques; computations; experimental results; filter bank structure; filter banks; full spectrum modeling; fullband CELP; performance improvement; rate change; signal sources; spectral modeling; speech codec; subband CELP; subspectral modeling; Bandwidth; Channel bank filters; Filter bank; Linear predictive coding; Predictive models; Signal resolution; Spectral analysis; Speech codecs; Speech coding; Transfer functions;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.476455

Filename

476455