Sound event localization and detection using a spatial omni-dimensional dynamic interactions network-Reference-Cited by-同舟云学术

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Sound event localization and detection using a spatial omni-dimensional dynamic interactions network

Published:2023-12-13 Issue: Volume: Page:
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Dao Tongyang,Guo Min,Ma Miao

Funder

the National Natural Science Foundation of China

the Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02901-8.pdf

Reference21 articles.

1. Stowell, D., Wood, M.D., Pamuła, H., Stylianou, Y., Glotin, H.: Automatic acoustic detection of birds through deep learning: the first bird audio detection challenge. Meth. Ecol. Evol. 10(3), 368–380 (2019)

2. Foggia, P., Petkov, N., Saggese, A., Strisciuglio, N., Vento, M.: Audio surveillance of roads: a system for detecting anomalous sounds. IEEE Trans. Intell. Transport. Syst. 17(1), 279–288 (2015)

3. Adavanne, S., Politis, A., Nikunen, J., Virtanen, T.: Sound event localization and detection of overlapping sources using convolutional recurrent neural networks. IEEE J. Sel. Topics Signal Process. 13(1), 34–48 (2018)

4. Lee, S.-H., Hwang, J.-W., Song, M.-H., Park, H.-M.: A method based on dual cross-modal attention and parameter sharing for polyphonic sound event localization and detection. Appl. Sci. 12(10), 5075 (2022)

5. Nguyen, T.N.T., Nguyen, N.K., Phan, H., Pham, L., Ooi, K., Jones, D.L., Gan, W.-S.: A general network architecture for sound event localization and detection using transfer learning and recurrent neural network. In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 935–939 (2021). IEEE

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