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Abstract-In the recent years, there have been an increasing amount of researches aiming at optimal beamforming with ad hoc microphone arrays, mostly fusion-center-based schemes. However, huge computational complexities and communication overheads impede many of these algorithms from being useful in practice. In this paper, we propose a low-footprint optimization approach to reduce the convergence time and overheads for the distributed beamforming problem. We transcribe the pseudocoherence-based beamforming which is insightful for taking into account the nature of speech. We formulate the distributed minimum variance distortionless response beamformer using the primal-dual method of multipliers. Our experiments confirm the fast convergence using the proposed distributed algorithm. It is also shown how a hard limit on the number of iterations affects the performance of the array in noise and interference suppression.Index Terms-Speech enhancement, ad hoc microphone array, distributed beamforming, primal-dual method of multipliers.

Speech enhancement is vital for improved listening practices. Ad hoc microphone arrays are promising assets for this purpose. Most well-established enhancement techniques with conventional arrays can be adapted into ad hoc scenarios. Despite recent efforts to introduce various ad hoc speech enhancement apparatus, a common framework for integration of conventional methods into this new scheme is still missing. This paper establishes such an abstraction based on inter and intra subarray speech coherencies. Along with measures for signal quality at the input of subarrays, a measure of coherency is proposed both for subarray selection in local enhancement approaches, and also for selecting a proper global reference when more than one subarray are used. Proposed methods within this framework are evaluated with regard to quantitative and qualitative measures, including array gains, the speech distortion ratio, the PESQ measure, and the STOI intelligibility measure. Major findings in this work are the observed changes in the superiority of different methods for certain conditions. When perceptual quality or intelligibility of the speech are the ultimate goals, there are turning points where the MVDR and the LCMV are superior to Wiener-based methods. Also, for certain scenarios, local approaches may be preferred to global ones.

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In this paper, a blind algorithm is proposed for speech enhancement in multi-speaker scenarios, in which interference rejection is the main objective. Here, the ad hoc array is broken into microphone duples which are used to partition the array into local sub-arrays. The core algorithm takes advantage of differences in signal structure in each duple. A geometric mean filter is then used to merge the output signals obtained with different duples, and to form a global broadband maximum signal-to-interference ratio (SIR) enhancement apparatus. The resulting filter outputs are enhanced acoustic signals in terms of SIR, as shown with experiments.