Beamforming using uniform circular arrays for distant speech recognition in reverberant environments and double talk scenarios

Pessentheiner, Hannes; Petrik, Stefan; Romsdorfer, Harald

doi:10.21437/interspeech.2012-394

Cited by 6 publications

(3 citation statements)

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“…[29]), as demonstrated in section VI. While this approach is based on a heuristic and optimality of its results is not guaranteed, it has been successfully applied in the past decades to a wide range of optimization problems related to antenna [29] and microphone [30] array design.…”

Section: A Optimal Microphone Positioningmentioning

confidence: 99%

“…Matrix Λ = diag{λ 1 , λ 2 , ..., λ L } cite 6 / 12 6 holds the eigenvalues of E pp H , as in (11). From (30), the eigenvalues {λ i } are given by:…”

Section: Relation To Doa Estimation Accuracymentioning

confidence: 99%

“…where Ωj is the MUSIC estimator of Ω j , h j is the j th column of H, being the steering vector of the array for the direction Ω j , and {u i } D i=1 are the first D left singular vectors of H, which, from (30), are also the eigenvectors of E pp H . By summing estimation error variances over all D sources, we obtain:…”

Section: Relation To Doa Estimation Accuracymentioning

confidence: 99%

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Theoretical Framework for the Optimization of Microphone Array Configuration for Humanoid Robot Audition

Tourbabin

Rafaely

2014

IEEE/ACM Trans. Audio Speech Lang. Process.

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An important aspect of a humanoid robot is audition. Previous work has presented robot systems capable of sound localization and source segregation based on microphone arrays with various configurations. However, no theoretical framework for the design of these arrays has been presented. In the current paper, a design framework is proposed based on a novel array quality measure. The measure is based on the effective rank of a matrix composed of the generalized head related transfer functions (GHRTFs) that account for microphone positions other than the ears. The measure is shown to be theoretically related to standard array performance measures such as beamforming robustness and DOA estimation accuracy. Then, the measure is applied to produce sample designs of microphone arrays. Their performance is investigated numerically, verifying the advantages of array design based on the proposed theoretical framework.

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Section: A Optimal Microphone Positioningmentioning

confidence: 99%

“…Matrix Λ = diag{λ 1 , λ 2 , ..., λ L } cite 6 / 12 6 holds the eigenvalues of E pp H , as in (11). From (30), the eigenvalues {λ i } are given by:…”

Section: Relation To Doa Estimation Accuracymentioning

confidence: 99%

Section: Relation To Doa Estimation Accuracymentioning

confidence: 99%

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