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Improving sound event detection through enhanced feature extraction and attention mechanisms

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References

  1. Li Y F, Liang D M. Safe semi-supervised learning: a brief introduction. Frontiers of Computer Science, 2019, 13(4): 669–676

    MATH  Google Scholar 

  2. Ji Z, Ni J, Liu X, Pang Y. Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning. Frontiers of Computer Science, 2023, 17(2): 172312

    Google Scholar 

  3. Nam H, Kim S H, Ko B Y, Park Y H. Frequency dynamic convolution: frequency-adaptive pattern recognition for sound event detection. In: Proceedings of the 23rd Annual Conference of the International Speech Communication Association. 2022, 2763–2767

    MATH  Google Scholar 

  4. Xiao S, Zhang X, Zhang P. Multi-dimensional frequency dynamic convolution with confident mean teacher for sound event detection. In: Proceedings of ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2023, 1–5

    MATH  Google Scholar 

  5. Chen S, Wu Y, Wang C, Liu S, Tompkins D, Chen Z, Che W, Yu X, Wei F. BEATs: audio pre-training with acoustic tokenizers. In: Proceedings of the 40th International Conference on Machine Learning. 2023, 5178–5193

    MATH  Google Scholar 

  6. Chen Y, Dai X, Liu M, Chen D, Yuan L, Liu Z. Dynamic convolution: attention over convolution kernels. In: Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020, 11027–11036

    MATH  Google Scholar 

  7. Li K, Cai P, Song Y. Li USTC team’s submission for DCASE 2023 challenge task4a. Technical Report, DCASE2023 Challenge, 2023

    MATH  Google Scholar 

  8. Li K, Song Y, Dai L R, McLoughlin I, Fang X, Liu L. AST-SED: an effective sound event detection method based on audio spectrogram transformer. In: Proceedings of ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2023, 1–5

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Zhejiang Provincial Key R&D Program (Nos. 2024C01108, 2023C01030, 2023C01034), the Hangzhou Key R&D Program (Nos. 2023SZD0046, 2024SZD1A03), and the Ningbo Key R&D Program (No. 2024Z114).

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Authors and Affiliations

  1. College of Information Engineering, China Jiliang University, Hangzhou, 310018, China

    Dongping Zhang, Siyi Wu & Jiabin Yu

  2. Hangzhou Hikvision Digital Technology Co., Ltd, Hangzhou, 310051, China

    Zhanhong Lu

  3. Hangzhou Aihua Intelligent Technology Co., Ltd, Hangzhou, 311422, China

    Zhehao Zhang

  4. Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China

    Haimiao Hu

Authors
  1. Dongping Zhang
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  2. Siyi Wu
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  3. Zhanhong Lu
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  4. Zhehao Zhang
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  6. Jiabin Yu
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Corresponding author

Correspondence to Dongping Zhang.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

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Zhang, D., Wu, S., Lu, Z. et al. Improving sound event detection through enhanced feature extraction and attention mechanisms. Front. Comput. Sci. 19, 1910707 (2025). https://doi.org/10.1007/s11704-025-41108-7

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  • DOI: https://doi.org/10.1007/s11704-025-41108-7