Direction of arrival estimation of sound sources using icosahedral CNNs
D Diaz-Guerra, A Miguel… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
In this paper, we present a new model for Direction of Arrival (DOA) estimation of sound
sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-
PHAT power maps computed from the signals received by a microphone array. This
icosahedral CNN is equivariant to the 60 rotational symmetries of the icosahedron, which
represent a good approximation of the continuous space of spherical rotations, and can be
implemented using standard 2D convolutional layers, having a lower computational cost …
sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-
PHAT power maps computed from the signals received by a microphone array. This
icosahedral CNN is equivariant to the 60 rotational symmetries of the icosahedron, which
represent a good approximation of the continuous space of spherical rotations, and can be
implemented using standard 2D convolutional layers, having a lower computational cost …
Direction of Arrival Estimation of Sound Sources Using Icosahedral CNNs
D Diaz-Guerra Aparicio, A Miguel, JR Beltran - 2023 - trepo.tuni.fi
In this paper, we present a new model for Direction of Arrival (DOA) estimation of sound
sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-
PHAT power maps computed from the signals received by a microphone array. This
icosahedral CNN is equivariant to the 60 rotational symmetries of the icosahedron, which
represent a good approximation of the continuous space of spherical rotations, and can be
implemented using standard 2D convolutional layers, having a lower computational cost …
sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-
PHAT power maps computed from the signals received by a microphone array. This
icosahedral CNN is equivariant to the 60 rotational symmetries of the icosahedron, which
represent a good approximation of the continuous space of spherical rotations, and can be
implemented using standard 2D convolutional layers, having a lower computational cost …
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