The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Sound event detection using spatial features and convolutional recurrent neural network
Open accessAbstract
This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle more than one type of these multichannel features by learning from each of them separately in the initial stages. We show that instead of concatenating the features of each channel into a single feature vector the network learns sound events in multichannel audio better when they are presented as separate layers of a volume. Using the proposed spatial features over monaural features on the same network gives an absolute F-score improvement of 6.1% on the publicly available TUT-SED 2016 dataset and 2.7% on the TUT-SED 2009 dataset that is fifteen times larger.
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Cites
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
The generalized correlation method for estimation of time delay
Knapp, C., & Carter, G. (1976) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1976.1162830 · Cited by 4,433 · cited 13×
“By using GCC-PHAT instead of TDOA, we take the data-oriented approach and get rid of empirical limitations and let the network learn the representation best suited for the problem.”
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Cited by
A State-of-the-Art Survey on Deep Learning Theory and Architectures
Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., Hasan, M., Van Essen, B. C., Awwal, A. A. S., & Asari, V. K. (2019) · Electronics · doi:10.3390/electronics8030292 · Cited by 1,620
Sound Event Detection: A tutorial
Mesaros, A., Heittola, T., Virtanen, T., & Plumbley, M. D. (2021) · IEEE Signal Processing Magazine · doi:10.1109/msp.2021.3090678 · Cited by 268
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Metadata
- Authors
- Adavanne, S., Pertila, P., & Virtanen, T.
- Venue
- 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Publisher
- IEEE
- Published
- 2017-03
- Pages
- 771-775
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2594627932
- Cited by
- 160
- References
- 2
- FWCI
- 13.90
- Type
- conference paper
- Language
- en
- Open access
- green
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- Adavanne, S., Pertila, P., & Virtanen, T. (2017). Sound event detection using spatial features and convolutional recurrent neural network. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/icassp.2017.7952260
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