Sound Event Localization and Detection Using Activity-Coupled Cartesian DOA Vector and RD3net

Reading the bibliography…

Fetching the paper…

Built on

N. Takahashi and Y. Mitsufuji, “D3Net: Densely connected multidilated DenseNet for music source separation,”
Original
2010
Earlier work this paper cites.
N. Takahashi, M. Gygli, B. Pfister, and L. V. Gool, “Deep convolutional neural networks and data augmentation for acoustic event detection,” in
2016
Earlier work this paper cites.
N. Takahashi, M. Gygli, and L. Van Gool, “Aenet: Learning deep audio features for video analysis,”
2017
Earlier work this paper cites.
V. Lostanlen, J. Salamon, M. Cartwright, B. McFee, A. Farnsworth, S. Kelling, and J. P. Bello, “Per-channel energy normalization: Why and how,”
2018
Earlier work this paper cites.
Z.-Q. Wang, J. Le Roux, and J. R. Hershey, “Multi-channel deep clustering: Discriminative spectral and spatial embeddings for speaker-independent speech separation,” in
2018
Earlier work this paper cites.

H. Erdogan and T. Yoshioka, “Investigations on data augmentation and loss functions for deep learning based speech-background separation,” in
Original
2018
Cited alongside, same era.
Y. Cao, Q. Kong, T. Iqbal, F. An, W. Wang, and M. D. Plumbley, “Polyphonic sound event detection and localization using a two-stage strategy,”
Original
2019
Cited alongside, same era.
L. Mazzon, Y. Koizumi, M. Yasuda, and N. Harada, “First order ambisonics domain spatial augmentation for dnn-based direction of arrival estimation,” in
2019
Cited alongside, same era.
D. S. Park, W. Chan, Y. Zhang, C.-C. Chiu, B. Zoph, E. D. Cubuk, and Q. V. Le, “SpecAugment: A simple data augmentation method for automatic speech recognition,”
2019
Cited alongside, same era.

J. Zhang, W. Ding, and L. He, “Data augmentation and prior knowledge-based regularization for sound event localization and detection,” in
2019
Later among the works it cites.
A. Mesaros, S. Adavanne, A. Politis, T. Heittola, and T. Virtanen, “Joint measurement of localization and detection of sound events,” in
2019
Later among the works it cites.
C. Ye, M. Evanusa, H. He, A. Mitrokhin, T. Goldstein, J. A. Yorke, C. Fermuller, and Y. Aloimonos, “Network deconvolution,” in
2020
Closest in time.
A. Politis, S. Adavanne, and T. Virtanen, “A dataset of reverberant spatial sound scenes with moving sources for sound event localization and detection,”
Original
2020
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…

Reading the bibliography…

Sound Event Localization and Detection Using Activity-Coupled Cartesian DOA Vector and RD3net · Around

N. Takahashi and Y. Mitsufuji, “D3Net: Densely connected multidilated DenseNet for music source separation,”
Original
2010
Earlier work this paper cites.
N. Takahashi, M. Gygli, B. Pfister, and L. V. Gool, “Deep convolutional neural networks and data augmentation for acoustic event detection,” in
2016
Earlier work this paper cites.
N. Takahashi, M. Gygli, and L. Van Gool, “Aenet: Learning deep audio features for video analysis,”
2017
Earlier work this paper cites.
V. Lostanlen, J. Salamon, M. Cartwright, B. McFee, A. Farnsworth, S. Kelling, and J. P. Bello, “Per-channel energy normalization: Why and how,”
2018
Earlier work this paper cites.
Z.-Q. Wang, J. Le Roux, and J. R. Hershey, “Multi-channel deep clustering: Discriminative spectral and spatial embeddings for speaker-independent speech separation,” in
2018
Earlier work this paper cites.

H. Erdogan and T. Yoshioka, “Investigations on data augmentation and loss functions for deep learning based speech-background separation,” in
Original
2018
Cited alongside, same era.
Y. Cao, Q. Kong, T. Iqbal, F. An, W. Wang, and M. D. Plumbley, “Polyphonic sound event detection and localization using a two-stage strategy,”
Original
2019
Cited alongside, same era.
L. Mazzon, Y. Koizumi, M. Yasuda, and N. Harada, “First order ambisonics domain spatial augmentation for dnn-based direction of arrival estimation,” in
2019
Cited alongside, same era.
D. S. Park, W. Chan, Y. Zhang, C.-C. Chiu, B. Zoph, E. D. Cubuk, and Q. V. Le, “SpecAugment: A simple data augmentation method for automatic speech recognition,”
2019
Cited alongside, same era.

J. Zhang, W. Ding, and L. He, “Data augmentation and prior knowledge-based regularization for sound event localization and detection,” in
2019
Later among the works it cites.
A. Mesaros, S. Adavanne, A. Politis, T. Heittola, and T. Virtanen, “Joint measurement of localization and detection of sound events,” in
2019
Later among the works it cites.
C. Ye, M. Evanusa, H. He, A. Mitrokhin, T. Goldstein, J. A. Yorke, C. Fermuller, and Y. Aloimonos, “Network deconvolution,” in
2020
Closest in time.
A. Politis, S. Adavanne, and T. Virtanen, “A dataset of reverberant spatial sound scenes with moving sources for sound event localization and detection,”
Original
2020
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…