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Acoustic scene analysis by multiperspective sector-based sound field decomposition

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor McCormack, Leo
dc.contributor.author McCrea, Michael
dc.date.accessioned 2021-10-24T17:00:55Z
dc.date.available 2021-10-24T17:00:55Z
dc.date.issued 2021-10-19
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/110493
dc.description.abstract In this thesis, the performance of high-order sound field analysis by spatial filtering is evaluated in the context of 3D source localization. First, various factors in ‘sector- based’ processing—including analysis order, the presence of interfering noise, and source direction—are assessed using two key sound field indicators derived from intensimetric analysis: sound field diffuseness estimation and source direction-of- arrival (DoA) estimation. This carries forward to the evaluation of a 3D source localization technique which utilizes concurrent analyses from multiple receivers. The evaluation is carried out by simulation of ideal spherical harmonic receiver signals of sound fields comprised of fundamental components—a mixture of plane wave sound sources and an isotropic diffuse field—which adhere to an underlying plane wave model that has previously been characterized analytically. This model is then challenged with two scenarios: the presence of an interfering sound source, and an anisotropic, partially-correlated reverberant field. The high-order, sector- based approach to source localization is shown to be a consistent improvement upon the (first-order) method without spatial filtering, operating primarily through the principle of increasing the direct-to-diffuse (or signal-to-noise) energy ratio. However, numerous considerations must be taken if robust localization is to be performed over a large spatial extent. These include sector orientation, the arrangement and number of receivers, and estimation filtering and culling. Informed by the system performance under the tested conditions as well as the analytical model describing the sound field under the action of spatial filtering, optimization techniques are proposed, tested, and found to be successful under specified constraints. These include employing the diffuseness metric for weighted-DoA estimation in the localization task, an iterative approach localization using the estimated source distance to weight the contribution of DoA estimates, and a spatial sweep technique which applies a diffuseness constraint for DoA estimation culling which moves toward multisource localization. en
dc.format.extent 71
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Acoustic scene analysis by multiperspective sector-based sound field decomposition en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.subject.keyword spatial audio en
dc.subject.keyword sound field analysis en
dc.subject.keyword Ambisonics en
dc.subject.keyword HOA en
dc.subject.keyword spatial filtering en
dc.identifier.urn URN:NBN:fi:aalto-202110249671
dc.programme.major Acoustics and Audio Technology fi
dc.programme.mcode ELEC3030 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Pulkki, Ville
dc.programme CCIS - Master’s Programme in Computer, Communication and Information Sciences (TS2013) fi
dc.location P1 fi
local.aalto.electroniconly yes
local.aalto.openaccess yes

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