A High-Accuracy, Low-Latency Technique for Talker Localization in Reverberant Environments Using Microphone Arrays

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Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained With Noise Signals (2018, methodology): “phase transform (SRP-PHAT) [4], and multichannel cross correlation coefficient (MCCC) [5], iv) adaptive multichannel time delay estimation using blind system identification based methods [6], v) probabilistic model based methods such as maximum likelihood method [7] and vi) methods based on histogra”
Pyroomacoustics: A Python Package for Audio Room Simulation and Array Processing Algorithms (2017, methodology): “The DOA class is extended to implement several popular algorithms: the popular multiple signal classification (MUSIC) [13] and steered response power phase transform (SRP-PHAT) [14], as well as coherent signal subspace method (CSSM) [15], weighted average of signal subspaces (WAVES) [16], and test o”
Recognition of overlapping speech using digital MEMS microphone arrays (2013, methodology): “Speaker localisation is carried out by using a superdirective variant of the original steered response power (SRP-PHAT) method from [15, 16].”
Automatic analysis of multimodal group actions in meetings (2005, background): “[52], [53], which is a continuous, bounded value that indicates the activity of a particular location.”