Acoustic array corrections for coherence loss due to the wind tunnel shear layer conventional improved Problem area Out-of-flow acoustic array measurements in open jet wind tunnels are hampered by the presence of the turbulent shear layer. Signal coherence between pairs of microphones in the array

This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple

Abstract—Microphone arrays sample the sound field in both space and time with the major objective being the extraction of the signal propagating from a desired direction-of-arrival (DOA). In order to reconstruct a spatial sinusoid from a set of discrete samples, the spatial sampling must occur at a

The Huge Microphone Array(HMA) is a project that started in February 1994 to design, construct, debug, and test a real-time 512-microphone array system and to develop algorithms for use on it. Analysis of known algorithms made it clear that signal-processing performance of over 6 Gigaflops would

This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the recently proposed Spatial Observability Function based microphone array integration technique, a maximum likelihood estimator for the correct position

Microphone arrays on rigid spheres elegantly facilitate forming of higher-order spherical harmonic directivity patterns. Hereby, they also enable surround recording with height in higher-order Ambisonics [1]. While the

This report describes the processing algorithms and gives an overview of the hardware for the small microphone array unit in the IM2.RTMAP (Real-time Microphone Array Processing) project. The algorithms include techniques for speech enhancement, speaker localisation and speaker segmentation

Abstract—This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the recently proposed spatial observability function (SOF) based microphone array integration technique, a maximum likelihood estimator for the correct

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This paper proposes a post-filtering estimation scheme for mul-tichannel noise reduction. The proposed method extends and im-proves the existing Zelinski’s and, the most general and prominent, McCowan’s post-filtering methods that use the auto- and cross-spectral densities of the multichannel input signals to estimate the transfer function of the Wiener post-filter. A major drawback of these two speech enhancement algorithms is that the noise power spectrum at the beamformer’s output is over-estimated and there-fore the derived filters are sub-optimal in the Wiener sense. The proposed method deals with this problem and can be considered as an optimal post-filter that is appropriate for a wide variety of different noise fields. In experiments over real-noise multichannel recordings, the proposed technique is shown to obtain a significant headstart over the other methods in terms of signal-to-noise ratio and speech degradation measures. In addition it is used for ASR experiments where promising preliminary results are presented.