DOA and Pitch Estimation of Audio Sources using IAA-based Filtering

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Resumé

For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also outperforms other state-of-the-art methods. Finally, the applicability of the considered approach is verified on real data.
OriginalsprogEngelsk
Titel2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014)
Antal sider5
ForlagIEEE
Publikationsdatosep. 2014
Sider900-904
ISBN (Trykt)9781479946037
StatusUdgivet - sep. 2014
Begivenhed22nd European Signal Processing Conference - Lisbon, Portugal
Varighed: 1 sep. 20145 sep. 2014

Konference

Konference22nd European Signal Processing Conference
LandPortugal
ByLisbon
Periode01/09/201405/09/2014

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Direction of arrival
Covariance matrix

Emneord

  • direction-of-arrival
  • fundamental frequency
  • LCMV
  • iterative adaptive approach
  • high resolution

Citer dette

Jensen, J. R., & Christensen, M. G. (2014). DOA and Pitch Estimation of Audio Sources using IAA-based Filtering. I 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014) (s. 900-904). IEEE.
Jensen, Jesper Rindom ; Christensen, Mads Græsbøll. / DOA and Pitch Estimation of Audio Sources using IAA-based Filtering. 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014) . IEEE, 2014. s. 900-904
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title = "DOA and Pitch Estimation of Audio Sources using IAA-based Filtering",
abstract = "For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also outperforms other state-of-the-art methods. Finally, the applicability of the considered approach is verified on real speech.",
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Jensen, JR & Christensen, MG 2014, DOA and Pitch Estimation of Audio Sources using IAA-based Filtering. i 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014) . IEEE, s. 900-904, 22nd European Signal Processing Conference, Lisbon, Portugal, 01/09/2014.

DOA and Pitch Estimation of Audio Sources using IAA-based Filtering. / Jensen, Jesper Rindom; Christensen, Mads Græsbøll.

2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014) . IEEE, 2014. s. 900-904.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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T1 - DOA and Pitch Estimation of Audio Sources using IAA-based Filtering

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N2 - For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also outperforms other state-of-the-art methods. Finally, the applicability of the considered approach is verified on real speech.

AB - For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also outperforms other state-of-the-art methods. Finally, the applicability of the considered approach is verified on real speech.

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Jensen JR, Christensen MG. DOA and Pitch Estimation of Audio Sources using IAA-based Filtering. I 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014) . IEEE. 2014. s. 900-904