A fast least-square deconvolution algorithm for vocal tract cross section estimation

Author

Hu, Yu Hen ; Milenkovic, Paul H.

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

Volume

38

Issue

6

fYear

1990

fDate

6/1/1990 12:00:00 AM

Firstpage

921

Lastpage

924

Abstract

An efficient computation algorithm, based on unitary Jacobi-type rotations, is developed for fast least-square deconvolution. Specifically, this algorithm is able to solve a positive definite covariance matrix with a special Toeplitz structure in O(N²) operations instead of O(N³) operations. This algorithm, which takes advantage of the inherent structure of the underlying deconvolution problem, is guaranteed to be numerically stable since only unitary transformation is used. It is implemented on an experimental system for the estimation of human vocal tract cross-section. A significant gain in processing is observed

Keywords

matrix algebra; speech analysis and processing; speech synthesis; efficient computation algorithm; fast least-square deconvolution algorithm; numerically stable; positive definite covariance matrix; special Toeplitz structure; unitary Jacobi-type rotations; unitary transformation; vocal tract cross section estimation; Convolution; Covariance matrix; Deconvolution; Human voice; Linear systems; Signal processing; Signal processing algorithms; Speech; System identification; Zinc;

fLanguage

English

Journal_Title

Acoustics, Speech and Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

0096-3518

Type

jour

DOI

10.1109/29.56053

Filename

56053