Broadband DOA Estimation Using Convolutional Neural Networks Trained with Noise Signals

doi:doi:10.57702/5hajj0pw

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Broadband DOA Estimation Using Convolutional Neural Networks Trained with Noise Signals

A convolution neural network (CNN) based classiﬁcation method for broadband DOA estimation is proposed, where the phase com-ponent of the short-time Fourier transform coefﬁcients of the re-ceived microphone signals are directly fed into the CNN and the features required for DOA estimation are learned during training.

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Soumitro Chakrabarty, Emanu¨al A. P. Habets (2024). Dataset: Broadband DOA Estimation Using Convolutional Neural Networks Trained with Noise Signals. https://doi.org/10.57702/5hajj0pw

DOI retrieved: December 16, 2024

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.1109/WASPAA.2017.8170010
Author	Soumitro Chakrabarty
More Authors	Emanu¨al A. P. Habets