Acoustic spectral estimation using higher order statistics

Shlomo Dubnov, Naftali Tishby

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Assuming an auto regressive (AR) filter model driven by a non-Gaussian white noise we formulate a general parameter estimation problem. A maximum likelihood solution gives an AR estimate of the filter and the probability distribution function parameters for non-Gaussian input. The proposed method is optimal in the information theoretic sense, giving the most probable model for the source and filter under the higher order statistics constrains of the observed signal. Analysis of human singing voices and musical instruments is presented and its acoustic interpretation is discussed.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers
Pages1-5
Number of pages5
ISBN (Electronic)0818662751
DOIs
StatePublished - 1 Jan 1994
Externally publishedYes
Event12th IAPR International Conference on Pattern Recognition - Conference C: Signal Processing - Conference D: Parallel Computing, ICPR 1994 - Jerusalem, Israel
Duration: 9 Oct 199413 Oct 1994

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Conference

Conference12th IAPR International Conference on Pattern Recognition - Conference C: Signal Processing - Conference D: Parallel Computing, ICPR 1994
Country/TerritoryIsrael
CityJerusalem
Period9/10/9413/10/94

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Acoustic spectral estimation using higher order statistics'. Together they form a unique fingerprint.

Cite this