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Sven Fischer, Ericsson Eurolab (Germany)
Karl-Dirk Kammeyer, University of Bremen (Germany)
In this paper the implementation of a broadband beamformer which is built up by several harmonically nested subarrays for each octave band combined with optimal postfiltering is described. This method has the advantage of providing large sensor distances for the postfilter estimation by simultaneously controlling the directivity of the array. The selection of an optimal postfilter is discussed in detail and its estimation based on a Nuttall/Carter method for spectrum estimation is described. The resulting noise reduction system yields improved performance in diffuse noise fields and no distortions in the case of coherent direct path noise. Furthermore, the system is robust to steering misadjustment.
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James G. Ryan, National Research Council (Canada)
Rafik A. Goubran, Carleton University (Canada)
This paper describes the application of array optimization techniques to improving the near-field response of an arbitrary microphone array. The optimization exploits the differences in wavefront curvature between near-field and far-field sound sources and is suitable for reverberation reduction in small rooms. The optimum near-field beamformer provides increased array gain over that obtained from a uniformly weighted delay-and-sum beamformer.
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Osamu Hoshuyama, NEC (Japan)
Akihiko Sugiyama, NEC (Japan)
Akihiro Hirano, NEC (Japan)
This paper presents a new robust adaptive microphone array (AMA) and its evaluation in an echoic environment. The proposed AMA is a generalized sidelobe canceller equipped with a variable blocking matrix using coefficient-constrained adaptive filters, and a multiple-input canceller using norm-constrained adaptive filters (NCAFs). Because the NCAFs have selective nonlinearity in the relationship between coefficient norm and coefficient error, the proposed AMA has better spatial selectivity than the conventional AMA. Evaluation with real acoustic data captured in a room of 0.3-second reverberation time shows that the noise is suppressed by 19 dB. In subjective evaluation, the proposed AMA obtains 3.8 on a 5-point mean-opinion-score scale.
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Douglas E. Sturim, Brown University (U.S.A.)
Harvey F. Silverman, Brown University (U.S.A.)
Michael S. Brandstein, Harvard University (U.S.A.)
A method for tracking the positional estimates of multiple talkers in the operating region of an acoustic microphone array is presented. Initial talker location estimates are provided by a time-delay-based localization algorithm. These raw estimates are spatially smoothed by a Kalman filter derived from a set of potential source motion models. Data association techniques based on the estimate clusterings and source trajectories are incorporated to match location observations with individual talkers. Experimental results are presented for array recorded data using multiple talkers in a variety of scenarios.
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Michael S. Brandstein, Harvard University (U.S.A.)
Harvey F. Silverman, Brown University (U.S.A.)
Conventional time-delay estimators exhibit dramatic performance degradations in the presence of multipath signals. This limits their application in reverberant enclosures, particularly when the signal of interest is speech and it may not possible to estimate and compensate for channel effects prior to time-delay estimation. This paper details an alternative approach which reformulates the problem as a linear regression of phase data and then estimates the time-delay through minimization of a robust statistical error measure. The technique is shown to be less susceptible to room reverberation effects. Simulations are performed across a range of source placements and room conditions to illustrate the utility of the proposed time-delay estimation method relative to conventional methods.
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Jie Gu, HK University of Science & Tech. (Hong Kong)
Sze Fong Yau, HK University of Science & Tech. (Hong Kong)
This paper presents a new model-based adaptive noise cancellation system using loudspeaker array and error sensor array which can be used to reduce the noise in a specific three-dimensional region. First, open loop system transfer functions are designed using a theoretical propagation model. The transfer functions thus found are regarded as the nominal values for the complete system. Second, to compensate for deviations from the theoretical model, the transfer functions are adapted using error measures from error sensor array by LMS algorithm. Computer simulation results shows that our approach is effective for noise reduction in 3-D space. Experiments using real-time active noise control hardware also confirms the performance of the system.
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Wolfgang Täger, CNET (France)
Yannick Mahieux, CNET (France)
The use of microphone arrays for sound pickup in reverberant environments has been proposed by many authors. The observation on the M microphones can be decomposed into a spatially coherent and an incoherent part. The first one is due to perfect (plane or spherical) sound waves caused by the direct path and specular reflections, whereas the latter is caused by diffusion, diffraction, non-perfect reflections, electrical and quantization noise. In this paper we firstly present a deflation method to detect and localize spatially coherent waves from the measured impulse responses. In a second step the filters which model the source directivity and the reflecting materials are estimated. The model takes into account nearfield delay, range attenuation, microphone and source directivity as well as non trivial reflections.
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Alberto Gonzalez, UPV, Valencia (Spain)
Antonio Albiol, UPV, Valencia (Spain)
Stephen J. Elliott, ISVR, Southampton (U.K.)
This paper deals with Multiple Input Multiple Output systems for active control of acoustic signals. These systems are used when the acoustic field is complex and therefore a number of sensors are necessary to estimate the sound field and a number of sources to create the cancelling field. A steepest descent iterative algorithm is applied to minimise the p-norm of a vector composed by the output signals of a microphone array. The existing algorithms deal with the 2-norm of this vector. This paper describes a general framework that covers the existing systems and then it focuses on the (infinity)-norm minimisation algorithm. The minimax algorithm based on the (infinity)-norm minimises the output signal which has the greatest power. It is shown by means of simulations using measured data from a real room that the minimax algorithm leads to a more uniform final noise field than the existing algorithms.
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Jeong-Hyeon Yun, Yonsei University (Korea)
Dae-Hee Youn, Yonsei University (Korea)
Young-Cheol Park, Samsung Electronic (Korea)
In this paper, a new active noise control algorithm based on a delayless subband adaptive filter architecture is presented. Also, an on-line system identification method implemented in the subband structure is suggested. To implement the filtered-x LMS algorithm in the subband structure, the secondary path transfer function is decomposed into sets of subband functions. The two filter on-line modeling algorithm is then applied to each subband to estimate the secondary-path transfer function in a decomposed form. In this manner, the computational load for the on-line system identification is reduced by a factor 3 compared with the wideband approach. Simulation results are presented to show the efficiency of the new ANC algorithm and the performance of the on-line system identification scheme.
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Paul Strauch, University of Edinburgh (U.K.)
Bernard Mulgrew, University of Edinburgh (U.K.)
The problem in active noise control in a linear duct is examined. Essentially, a nonlinear inverse to a nonminimum phase actuator is proposed. The nonlinear inverse exploits the non-Gaussian nature of some chaotic and stochastic noise sources. The architecture of the controller is derived using Bayesian estimation theory and is shown to be a combination of a linear adaptive network and a radial basis function (RBF) or Volterra series (VS) network. Because of the nonlinear nature of the controller, the filtered-x least means square (LMS) architecture cannot be used. Hence a modified active noise controller is proposed. Simulation results demonstrate the improvements in performance achievable with the combined linear and nonlinear controller.
ic970395.pdf ic970395.pdf TOPScott C. Douglas, University of Utah (U.S.A.)
In some situations where active noise control could be used, the well-known multichannel version of the filtered-X LMS adaptive filter is too computationally-complex to implement. In this paper, we develop a fast, exact implementation of this multichannel system whose complexity is approximately O(2L) per filter channel, where L is the FIR filter length. In addition, we provide a computationally-efficient method for effectively removing the delays of the secondary paths within the coefficient updates, thus yielding a fast implementation of the LMS adaptive algorithm for multichannel active noise control. Examples illustrate both the equivalence of the algorithms to their original counterparts and the computational gains provided by the new algorithms.
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Toshifumi Kosakat, Tokyo National College of Technology (Japan)
Stephen J. Elliott, University of Southampton (U.K.)
Christopher C. Boucher, University of Southampton (U.K.)
A Frequency Domain implementation of the LMS Algorithm has significant advantages. In broadband applications it is important to use the correct window function before Fourier transformation to obtain an unbiased estimation of the required cross correlation function and to eliminate wrap-around effects. In the Frequency Domain Filtered-X LMS Algorithm described in this paper, the control filter is updated in the frequency domain as a background task, while control filtering is performed in time domain, to minimize processing delays. The frequency domain algorithm showed better performance than the conventional time domain algorithm in simulations of single channel active control systems. The algorithm is also able to improve the convergence of multiple channel systems by compensating for the coupling between the control channels.
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