Analysis of noise reduction and dereverberation techniques based on microphone arrays with postfiltering

Marro, Claude; Mahieux, Y.; Simmer, Klaus Uwe

doi:10.1109/89.668818

Cited by 202 publications

(112 citation statements)

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“…To compare our proposed method, we consider the methods in [9], [11] and [5]- [8]. In [9] and [11] the microphone positions are derived for symmetric and nonsymmetric beampatterns, respectively, by approximating a continuously distributed sensor.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In [9] and [11] the microphone positions are derived for symmetric and nonsymmetric beampatterns, respectively, by approximating a continuously distributed sensor. In [5]- [8] the microphone positions are computed by using the harmonic nesting approach.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The initializing microphone array is symmetric to satisfy condition (41) and is computed using the harmonic nested array method in [5]- [8] or the method in [9] 2 . The beamformer is obtained by solving the optimization problem in (37); to satisfy conditions (41) and (42), the linear-phase constraints in (43) and (45) are incorporated in the optimization.…”

Section: Design P(lp)mentioning

confidence: 99%

“…This is because the more widely separated sensors facilitate better performance at lower frequencies, while the closely spaced ones prevent spatial aliasing at higher frequencies. In [4]- [8], the microphone elements are arranged in the form of a nested array by appropriately combining several uniformlyspaced sub-arrays. Alternatively, in [9]- [11], the microphone positions are obtained by approximating a continuously distributed sensor as a discrete set of filtered broadband omnidirectional array elements.…”

Section: Introductionmentioning

confidence: 99%

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Design of minimax robust broadband beamformers with optimized microphone positions

Nongpiur¹

2014

Digital Signal Processing

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A new method for the design of robust minimax far-field broadband beamformers with optimized microphone positions is proposed. The method is formulated as an iterative optimization problem where the maximum passband 1 magnitude response error is minimized and the microphone positions are optimized while ensuring that the minimum stopband attenuation is above a prescribed level. To maintain robustness, we constrain a sensitivity parameter, namely, the white noise gain, to be above prescribed levels across the frequency band. An additional feature of the method, which is quite useful in certain applications, is that it provides the capability of constraining the gain in the transition band to always lie below the maximum gain in the passband. Performance comparisons with existing methods show that the optimization of the microphone positions results in beamformers with superior performance.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Design P(lp)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of minimax robust broadband beamformers with optimized microphone positions

Nongpiur¹

2014

Digital Signal Processing

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“…A quite common method for the formulation of the post-filter transfer function is based on the use of the auto-and cross-power spectral densities of the multichannel input signals [2,7,11]. One of the early methods for post-filter estimation is due to Zelinski [7], which was further studied by Marro et al [13]. The generalized version of Zelinski's algorithm is based on the assumption of a spatially uncorrelated noise field.…”

Section: Introductionmentioning

confidence: 99%