首页> 外文会议>2016 IEEE International Workshop on Acoustic Signal Enhancement >Multi-speaker DOA estimation in reverberation conditions using expectation-maximization
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Multi-speaker DOA estimation in reverberation conditions using expectation-maximization

机译:使用期望最大化的混响条件下的多扬声器DOA估计

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A novel direction of arrival (DOA) estimator for concurrent speakers in reverberant environment is presented. Reverberation, if not properly addressed, is known to degrade the performance of DOA estimators. In our contribution, the DOA estimation task is formulated as a maximum likelihood (ML) problem, which is solved using the expectation-maximization (EM) procedure. The received microphone signals are modelled as a sum of anechoic and reverberant components. The reverberant components are modelled by a timeinvariant coherence matrix multiplied by time-varying reverberation power spectral density (PSD). The PSDs of the anechoic speech and reverberant components are estimated as part of the EM procedure. It is shown that the DOA estimates, obtained by the proposed algorithm, are less affected by reverberation than competing algorithms that ignore the reverberation. Experimental study demonstrates the benefit of the presented algorithm in reverberant environment using measured room impulse responses (RIRs).
机译:提出了一种新的混响环境中同时讲话者的到达方向(DOA)估计器。如果不能正确解决混响问题,则会降低DOA估计器的性能。在我们的贡献中,DOA估计任务被表述为最大似然(ML)问题,可使用期望最大化(EM)程序解决。接收到的麦克风信号被建模为消声和混响分量的总和。混响分量通过时不变相干矩阵乘以时变混响功率谱密度(PSD)来建模。无声语音和混响分量的PSD被估计为EM程序的一部分。结果表明,与忽略混响的竞争算法相比,所提算法获得的DOA估计受混响的影响较小。实验研究表明,使用测得的房间脉冲响应(RIR),该算法在混响环境中的优势。

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