Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array

Despoina Pavlidi, Anthony Griffin, M. Puigt, A. Mouchtaris
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引用次数: 208

Abstract

In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these “single-source” zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.
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使用圆形麦克风阵列的实时多声源定位和计数
在这项工作中,提出了一种多声源定位和计数方法,该方法对源信号施加宽松的稀疏性约束。均匀圆形传声器阵列用于克服线性阵列的模糊性,但其基本概念(稀疏分量分析和基于估计直方图的匹配追踪操作)适用于任何传声器阵列拓扑。我们的方法是基于检测时频(TF)区域,其中一个源比其他源占优势。该方法利用在这些“单源”区域中适当选择的TF分量,通过对DOA估计直方图应用基于匹配追踪的方法,共同估计有效源的数量及其对应的到达方向(DOA)。该方法具有较好的DOA估计和源计数性能,且复杂度较低,非常适合于实时应用。通过模拟(在各种信噪比条件和混响环境中)和真实环境实验,我们表明,我们的方法在精度方面优于其他最先进的DOA和源计数方法,同时在计算复杂度方面显着提高效率。
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
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审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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