Optimum harmonics tracking filter for auditory scene analysis

Author

Nishi, Kazuki ; Ando, Shigeru ; Aida, Shuhei

Author_Institution

Dept. of Commun. & Syst. Eng., Univ. of Electro-Commun., Tokyo, Japan

Volume

1

fYear

1996

fDate

7-10 May 1996

Firstpage

573

Abstract

We propose a new harmonics tracking algorithm for auditory scene analysis. It extracts the most significant stream from multiple sound streams as well as the tracking of each harmonic components. For the optimum tracking of pitch candidates, a novel estimation technique based on nonlinear Kalman filtering and Parzen estimate (non-parametric Kalman filter, NPKF) is used. For invariant reconstruction of harmonic components against pitch estimation error, we perform a filtering process in the wavelet domain. Using simulated data and real world data, we show several experimental results for extracting the most dominant sound stream among multiple ones

Keywords

Kalman filters; filtering theory; harmonic analysis; nonlinear filters; optimisation; speech processing; tracking filters; wavelet transforms; Parzen estimate; auditory scene analysis; estimation technique; harmonics tracking filter; invariant reconstruction; most dominant sound stream; most significant stream extraction; multiple sound streams; non-parametric Kalman filter; nonlinear Kalman filtering; optimum tracking; pitch candidates; pitch estimation error; pitch likelihood function; speech; wavelet domain; Filter bank; Filtering; Finite impulse response filter; Frequency estimation; IIR filters; Image analysis; Kalman filters; Power harmonic filters; Target tracking; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.541161

Filename

541161