The Experts below are selected from a list of 11067 Experts worldwide ranked by ideXlab platform

Lieven De Strycker - One of the best experts on this subject based on the ideXlab platform.

  • An ultra-low-power omnidirectional MEMS Microphone Array for wireless acoustic sensors
    2017 IEEE SENSORS, 2017
    Co-Authors: Bart Thoen, Geoffrey Ottoy, Lieven De Strycker
    Abstract:

    This paper presents an omnidirectional ultra low-power MEMS Microphone Array for use in low-power distributed wireless sensor networks. The Microphone Array is used for determining the Angle-of-Arrival (AoA) of sound events in an indoor environment. When the angles, measured by several wireless sensor nodes, are combined, a sound event can be located. This Array consisting of 4 Microphone elements, each with their own switchable two-stage amplifier, is completely configurable using an on board low-power microcontroller. This means that only the necessary elements are active when they are actually needed. Due to the selection of ultra low-power components and smart switching, the power consumption of the Array is much lower than other similar designs, consuming only 0.8 mW when the Array is activated and 66 nW during sleep.

  • a low power mems Microphone Array for wireless acoustic sensors
    Static Analysis Symposium, 2016
    Co-Authors: Geoffrey Ottoy, Bart Thoen, Lieven De Strycker
    Abstract:

    In this article we present the design of a low-power MEMS Microphone Array for wireless sensors. The Array is used as part of a device that performs acoustic Angle-Of-Arrival (AOA) measurements. The power consumption of this design is lower than that of comparable designs. Each of the 4 analog channels (each with a Microphone and amplifier) can be turned on or off (standby) separately. The power consumption is 1.8 mW per channel, and about 0.13 μW in standby. For a single AOA detection cycle (Array activation, audio sampling, AOA computation), the energy consumption is 6.02 mJ. When consecutive AOA detections are performed, the energy cost per detection converges to 3.20 mJ. The AOA accuracy corresponds with the expectations. With a mean error of 4°, this is lower than that of comparable designs.

De Strycker Lieven - One of the best experts on this subject based on the ideXlab platform.

  • An ultra-low-power omnidirectional MEMS Microphone Array for wireless acoustic sensors
    IEEE, 2017
    Co-Authors: Thoen Bart, Ottoy Geoffrey, De Strycker Lieven
    Abstract:

    This paper presents an omnidirectional ultra low-power MEMS Microphone Array for use in low-power distributed wireless sensor networks. The Microphone Array is used for determining the Angle-of-Arrival (AoA) of sound events in an indoor environment. When the angles, measured by several wireless sensor nodes, are combined, a sound event can be located. This Array consisting of 4 Microphone elements, each with their own switchable two-stage amplifier, is completely configurable using an on board low-power microcontroller. This means that only the necessary elements are active when they are actually needed. Due to the selection of ultra low-power components and smart switching, the power consumption of the Array is much lower than other similar designs, consuming only 0.8 mW when the Array is activated and 66 nW during sleep.status: publishe

  • A Low-Power MEMS Microphone Array for Wireless Acoustic Sensors
    'Institute of Electrical and Electronics Engineers (IEEE)', 2016
    Co-Authors: Ottoy Geoffrey, Thoen Bart, De Strycker Lieven
    Abstract:

    In this article we present the design of a low-power MEMS Microphone Array for wireless sensors. The Array is used as part of a device that performs acoustic Angle-Of-Arrival (AOA) measurements. The power consumption of this design is lower than that of comparable designs. Each of the 4 analog channels (each with a Microphone and amplifier) can be turned on or off (standby) separately. The power consumption is 1.8 mW per channel, and about 0.13 ??W in standby. For a single AOA detection cycle (Array activation, audio sampling, AOA computation), the energy consumption is 6.02 mJ. When consecutive AOA detections are performed, the energy cost per detection converges to 3.20 mJ. The AOA accuracy corresponds with the expectations. With a mean error of 4??, this is lower than that of comparable designs.status: publishe

Herve Bourlard - One of the best experts on this subject based on the ideXlab platform.

  • enhanced diffuse field model for ad hoc Microphone Array calibration
    Signal Processing, 2014
    Co-Authors: Mohammad J Taghizadeh, Philip N Garner, Herve Bourlard
    Abstract:

    In this paper, we investigate the diffuse field coherence model for Microphone Array pairwise distance estimation. We study the fundamental constraints and assumptions underlying this approach and propose evaluation methodologies to measure the adequacy of diffuseness for Microphone Array calibration. In addition, an enhanced schemebased on coherence averaging and histogramming, is presented to improve the robustness and performance of the pairwise distance estimation approach. The proposed theories and algorithms are evaluated on simulated and real data recordings for calibration of Microphone Array geometry in an ad hoc set-up. HighlightsAveraging and histogramming improve the diffuse field coherence model for calibration.A novel approach for assessment of the adequacy of diffuseness is formulated.The relation between distance, enclosure dimension and diffuseness is characterized.A methodology for augmenting the diffuse sound field is proposed.Fundamental limitation of calibration based on the coherence model is analyzed.

  • euclidean distance matrix completion for ad hoc Microphone Array calibration
    International Conference on Digital Signal Processing, 2013
    Co-Authors: Mohammad J Taghizadeh, Reza Parhizkar, Philip N Garner, Herve Bourlard
    Abstract:

    This paper addresses the application of missing data recovery via matrix completion for audio sensor networks. We propose a method based on Euclidean distance matrix completion for ad-hoc Microphone Array location calibration. This method can calibrate a full network from partial connectivity information. The pairwise distances of Microphones in close proximity are estimated using the coherence model of the diffuse noise field. The distance matrix of the ad-hoc network is constructed where the distances of the Microphones above a threshold are missing. We exploit the low-rank property of the squared distance matrix and apply a matrix completion method to recover the missing entries. In order to constrain the Euclidean space geometry, we propose the additional use of the Cadzow algorithm for matrix completion. The applicability of the proposed method is evaluated on real data recordings where a significant improvement over the state-of-the-art is achieved.

  • Microphone Array post filter for diffuse noise field
    International Conference on Acoustics Speech and Signal Processing, 2002
    Co-Authors: Iain Mccowan, Herve Bourlard
    Abstract:

    This paper proposes a novel technique for estimating the signal power spectral density to be used in the transfer function of a Microphone Array post-filter. The technique is a modification of the existing Zelinski post-filter, which uses the auto- and cross-spectral densities of the Array inputs to estimate the signal and noise spectral densities. The Zelinski technique, however, assumes zero cross-correlation between noise on different sensors. This assumption is inaccurate in real conditions, particularly at low frequencies and for Arrays with closely spaced sensors. In this paper we replace this with an assumption of a theoretically diffuse noise field, which is more appropriate in a variety of realistic noise environments. In experiments using noise recordings from an office of computer workstations, the modified post-filter results in significant improvement in terms of objective speech quality measures and speech recognition performance.

Boaz Rafaely - One of the best experts on this subject based on the ideXlab platform.

  • Microphone Array Signal Processing for Robot Audition
    2017
    Co-Authors: Heinrich Löllmann, Boaz Rafaely, Alastair Moore, Patrick Naylor, Radu Horaud, Alexandre Mazel, Walter Kellermann
    Abstract:

    Robot audition for humanoid robots interacting naturally with humans in an unconstrained real-world environment is a hitherto unsolved challenge. The recorded Microphone signals are usually distorted by background and interfering noise sources (speakers) as well as room reverberation. In addition, the movements of a robot and its actuators cause ego-noise which degrades the recorded signals significantly. The movement of the robot body and its head also complicates the detection and tracking of the desired, possibly moving , sound sources of interest. This paper presents an overview of the concepts in Microphone Array processing for robot audition and some recent achievements.

  • Localization of multiple speakers under high reverberation using a spherical Microphone Array and the direct-path dominance test
    IEEE Transactions on Audio Speech and Language Processing, 2014
    Co-Authors: Or Nadiri, Boaz Rafaely
    Abstract:

    One of the major challenges encountered when localizing multiple speakers in real world environments is the need to overcome the effect of multipath distortion due to room reverberation. A wide range of methods has been proposed for speaker localization, many based on Microphone Array processing. Some of these methods are designed for the localization of coherent sources, typical of multipath environments, and some have even reported limited robustness to reverberation. Nevertheless, speaker localization under conditions of high reverberation still remains a challenging task. This paper proposes a novel multiple-speaker localization technique suitable for environments with high reverberation, based on a spherical Microphone Array and processing in the spherical harmonics (SH) domain. The non-stationarity and sparsity of speech, as well as frequency smoothing in the SH domain, are exploited in the development of a direct-path dominance test. This test can identify time-frequency (TF) bins that contain contributions from only one significant source and no significant contribution from room reflections, such that localization based on these selected TF-bins is performed accurately, avoiding the potential distortion due to other sources and reverberation. Computer simulations and an experiment in a real reverberant room validate the robustness of the proposed method in the presence of high reverberation .

  • Near-Field Spherical Microphone Array Processing With Radial Filtering
    IEEE Transactions on Audio Speech and Language Processing, 2011
    Co-Authors: Etan Fisher, Boaz Rafaely
    Abstract:

    This paper presents an analysis of spherical Microphone Array capabilities in the near-field, with an emphasis on radial filtering of sources in a given direction. The near-field of the Array is defined in terms of frequency and distance from the Array. Directional beamforming is demonstrated given the near-field radial compensation filter, which yields a desired directional beampattern at a chosen distance from the Array. This pattern deteriorates as the source draws away from the Array. Next, a framework is presented for radial filter design, enabling distance discrimination between sources positioned in the same direction relative to the Array. Design examples include Dolph-Chebyshev radial filtering, radial notch filtering, and numerical design. Performance is analyzed in terms of spatial response and robustness to noise. Results show radial filtering is practical for improving attenuation of far-field and near-field interfering sources relative to a desired source positioned in the same direction.

  • dolph chebyshev radial filter for the near field spherical Microphone Array
    Workshop on Applications of Signal Processing to Audio and Acoustics, 2009
    Co-Authors: Etan Fisher, Boaz Rafaely
    Abstract:

    When close enough to a Microphone Array, the spherical nature of radiating sources allows for sound field processing in terms of distance as well as direction. As part of an on-going study on beamforming given sources close to a spherical Microphone Array, sound field processing is examined through the use of radial filters. In this paper, a radial Dolph-Chebyshev design is presented for attenuating far-field interference given sources close to the Array surface. The proposed radial filter facilitates an analytical formulation of the design technique, and may be practical for sources very close to the Array surface.

  • Microphone Array signal processing
    2008
    Co-Authors: Boaz Rafaely
    Abstract:

    This article reviews Microphone Array Signal Processing by Jacob Benesty, Jingdong Chen, Yiteng Huang , Berlin, 2008. 240 pp. price $119 (hardcover). ISBN: 3540786112

Marc Moonen - One of the best experts on this subject based on the ideXlab platform.

  • An integrated MVDR beamformer for speech enhancement using a local Microphone Array and external Microphones
    EURASIP Journal on Audio Speech and Music Processing, 2021
    Co-Authors: Randall Ali, Toon Waterschoot, Marc Moonen
    Abstract:

    An integrated version of the minimum variance distortionless response (MVDR) beamformer for speech enhancement using a Microphone Array has been recently developed, which merges the benefits of imposing constraints defined from both a relative transfer function (RTF) vector based on a priori knowledge and an RTF vector based on a data-dependent estimate. In this paper, the integrated MVDR beamformer is extended for use with a Microphone configuration where a Microphone Array, local to a speech processing device, has access to the signals from multiple external Microphones (XMs) randomly located in the acoustic environment. The integrated MVDR beamformer is reformulated as a quadratically constrained quadratic program (QCQP) with two constraints, one of which is related to the maximum tolerable speech distortion for the imposition of the a priori RTF vector and the other related to the maximum tolerable speech distortion for the imposition of the data-dependent RTF vector. An analysis of how these maximum tolerable speech distortions affect the behaviour of the QCQP is presented, followed by the discussion of a general tuning framework. The integrated MVDR beamformer is then evaluated with audio recordings from behind-the-ear hearing aid Microphones and three XMs for a single desired speech source in a noisy environment. In comparison to relying solely on an a priori RTF vector or a data-dependent RTF vector, the results demonstrate that the integrated MVDR beamformer can be tuned to yield different enhanced speech signals, which may be more suitable for improving speech intelligibility despite changes in the desired speech source position and imperfectly estimated spatial correlation matrices.

  • energy based multi speaker voice activity detection with an ad hoc Microphone Array
    International Conference on Acoustics Speech and Signal Processing, 2010
    Co-Authors: Alexander Bertrand, Marc Moonen
    Abstract:

    In this paper, we propose an energy-based technique to track the power of multiple simultaneous speakers using an ad hoc Microphone Array with unknown Microphone positions. By considering the short-term power of the Microphone signals, the problem can be converted into a non-negative blind source separation (NBSS) problem. By exploiting the prior knowledge that the source signals are non-negative and well-grounded, very efficient algorithms can be used to solve this NBSS problem, based only on second order statistics. We provide simulation results that demonstrate the effectiveness of the presented algorithm.

  • design of broadband beamformers robust against gain and phase errors in the Microphone Array characteristics
    IEEE Transactions on Signal Processing, 2003
    Co-Authors: Simon Doclo, Marc Moonen
    Abstract:

    Fixed broadband beamformers using small-size Microphone Arrays are known to be highly sensitive to errors in the Microphone Array characteristics. The paper describes two design procedures for designing broadband beamformers with an arbitrary spatial directivity pattern, which are robust against gain and phase errors in the Microphone Array characteristics. The first design procedure optimizes the mean performance of the broadband beamformer and requires knowledge of the gain and the phase probability density functions, whereas the second design procedure optimizes the worst-case performance by using a minimax criterion. Simulations with a small-size Microphone Array show the performance improvement that can be obtained by using a robust broadband beamformer design procedure.