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Causal MSE-Optimal Filters for Personal Audio Subject to Constrained Contrast
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group. Dirac Res AB, S-75320 Uppsala, Sweden.
2019 (English)In: IEEE-ACM Transactions on Audio, Speech and Language Processing (TASLP), ISSN 2329-9290, Vol. 27, no 5, p. 972-987Article in journal (Refereed) Published
Abstract [en]

A novel design method that generates causal pre-compensation filters is formulated. The resulting filters are constrained with respect to the amount of acoustic contrast they generate and are intended to be used for personal audio. The proposed method provides a more direct method for trading bright zone behavior against acoustic contrast as compared to other causal methods available. It also provides improved control over the temporal properties of the resulting filters as compared to the pre-existing non-causal methods. The resulting filters are analyzed by means of simulations, based on measured impulse responses of the sound-system-room interactions. The results of the simulations are compared to simulations of a frequency-domain optimal method with comparable objective, as proposed by Cai et al. and the results of the comparison are explained using the design equations. It is shown that the proposed method is viable, but that unattainable contrasts have a detrimental impact on the spectral bright zone behavior. A few different strategies for dealing with this problem are also proposed. It is demonstrated that the detrimental effect of increasingly strict causality constraints mainly concerns the lower frequency bright zone behavior in the system under investigation, but that the very highest attainable contrast levels may also be reduced somewhat.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 27, no 5, p. 972-987
Keywords [en]
Signal processing, acoustic signal processing, filters, IIR filters
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-382546DOI: 10.1109/TASLP.2019.2904839ISI: 000464139400005OAI: oai:DiVA.org:uu-382546DiVA, id: diva2:1314985
Funder
Swedish Research Council, 621-2014-5871Knut and Alice Wallenberg FoundationAvailable from: 2019-05-10 Created: 2019-05-10 Last updated: 2019-05-10Bibliographically approved

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CiteExportLink to record
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Citation style
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