Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation

Research output: Contribution to journalJournal articleResearchpeer-review

7 Citations (Scopus)
375 Downloads (Pure)

Abstract

In this paper, spatio-temporal filtering methods are proposed for estimating the direction-of-arrival (DOA) and fundamental frequency of periodic signals, like those produced by the speech production system and many musical instruments using microphone arrays. This topic has quite recently received some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed iterative adaptive approach (IAA). Experiments demonstrate the improved performance of the proposed methods under adverse conditions compared to the state of the art using both synthetic signals and real signals, as well as illustrate the properties of the methods and the filters.
Original languageEnglish
JournalI E E E Transactions on Audio, Speech and Language Processing
Volume23
Issue number1
Pages (from-to)174-185
Number of pages12
ISSN1558-7916
DOIs
Publication statusPublished - Jan 2015

Fingerprint

Frequency estimation
Direction of arrival
arrivals
estimators
Musical instruments
estimating
Adaptive filters
Microphones
Beamforming
Covariance matrix
adaptive filters
beamforming
microphones
filters
Experiments

Keywords

  • Fundamental frequency estimation
  • DOA estimation
  • joint estimation
  • 2-D filtering
  • LCMV beamformer
  • periodogram-based beamformer

Cite this

@article{19ead501740141ababbd99bed34a8ec0,
title = "Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation",
abstract = "In this paper, spatio-temporal filtering methods are proposed for estimating the direction-of-arrival (DOA) and fundamental frequency of periodic signals, like those produced by the speech production system and many musical instruments using microphone arrays. This topic has quite recently received some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed iterative adaptive approach (IAA). Experiments demonstrate the improved performance of the proposed methods under adverse conditions compared to the state of the art using both synthetic signals and real signals, as well as illustrate the properties of the methods and the filters.",
keywords = "fundamental frequency estimation, DOA estimation, joint estimation, 2-D filtering, LCMV beamformer, periodogram-based beamformer, Fundamental frequency estimation, DOA estimation, joint estimation, 2-D filtering, LCMV beamformer, periodogram-based beamformer",
author = "Jensen, {Jesper Rindom} and Christensen, {Mads Gr{\ae}sb{\o}ll} and Jacob Benesty and Jensen, {S{\o}ren Holdt}",
year = "2015",
month = "1",
doi = "10.1109/TASLP.2014.2377583",
language = "English",
volume = "23",
pages = "174--185",
journal = "IEEE/ACM Transactions on Audio, Speech, and Language Processing",
issn = "2329-9290",
publisher = "IEEE Signal Processing Society",
number = "1",

}

Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation. / Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob; Jensen, Søren Holdt.

In: I E E E Transactions on Audio, Speech and Language Processing, Vol. 23, No. 1, 01.2015, p. 174-185.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation

AU - Jensen, Jesper Rindom

AU - Christensen, Mads Græsbøll

AU - Benesty, Jacob

AU - Jensen, Søren Holdt

PY - 2015/1

Y1 - 2015/1

N2 - In this paper, spatio-temporal filtering methods are proposed for estimating the direction-of-arrival (DOA) and fundamental frequency of periodic signals, like those produced by the speech production system and many musical instruments using microphone arrays. This topic has quite recently received some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed iterative adaptive approach (IAA). Experiments demonstrate the improved performance of the proposed methods under adverse conditions compared to the state of the art using both synthetic signals and real signals, as well as illustrate the properties of the methods and the filters.

AB - In this paper, spatio-temporal filtering methods are proposed for estimating the direction-of-arrival (DOA) and fundamental frequency of periodic signals, like those produced by the speech production system and many musical instruments using microphone arrays. This topic has quite recently received some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed iterative adaptive approach (IAA). Experiments demonstrate the improved performance of the proposed methods under adverse conditions compared to the state of the art using both synthetic signals and real signals, as well as illustrate the properties of the methods and the filters.

KW - fundamental frequency estimation

KW - DOA estimation

KW - joint estimation

KW - 2-D filtering

KW - LCMV beamformer

KW - periodogram-based beamformer

KW - Fundamental frequency estimation

KW - DOA estimation

KW - joint estimation

KW - 2-D filtering

KW - LCMV beamformer

KW - periodogram-based beamformer

U2 - 10.1109/TASLP.2014.2377583

DO - 10.1109/TASLP.2014.2377583

M3 - Journal article

VL - 23

SP - 174

EP - 185

JO - IEEE/ACM Transactions on Audio, Speech, and Language Processing

JF - IEEE/ACM Transactions on Audio, Speech, and Language Processing

SN - 2329-9290

IS - 1

ER -