Direction of arrival estimation of sound sources using icosahedral CNNs
| Autor: | David Diaz-Guerra, Antonio Miguel, Jose R. Beltran |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Signal Processing (eess.SP)
FOS: Computer and information sciences Sound (cs.SD) Computer Science - Machine Learning Acoustics and Ultrasonics Computer Science - Sound Machine Learning (cs.LG) Computational Mathematics Audio and Speech Processing (eess.AS) Computer Science (miscellaneous) FOS: Electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Electrical Engineering and Systems Science - Signal Processing Electrical Engineering and Systems Science - Audio and Speech Processing |
| Popis: | 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 than most of the spherical CNNs. In addition, instead of using fully connected layers after the icosahedral convolutions, we propose a new soft-argmax function that can be seen as a differentiable version of the argmax function and allows us to solve the DOA estimation as a regression problem interpreting the output of the convolutional layers as a probability distribution. We prove that using models that fit the equivariances of the problem allows us to outperform other state-of-the-art models with a lower computational cost and more robustness, obtaining root mean square localization errors lower than 10{\deg} even in scenarios with a reverberation time $T_{60}$ of 1.5 s. Comment: The code to reproduce this work can be found in our GitHub repository: https://github.com/DavidDiazGuerra/icoDOA |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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