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- W2999896480 abstract "In the sound environment of instability noise, the recognition rate of sound events would be reduced if using a single sound feature to train public sound data. To solve this problem, we propose a new method of sound event recognition based in feature combination with low SNR in this paper. It improves the recognition of sound events in real scenes by adding noise to public sound data sets. On the other hand, in order to overcome the inaccuracy of single features in noise recognition and significantly improved the recognition rate, we propose a new combination method which combining multiple features and drawing on the advantages of image recognition. Actual test shows that the public sound data set with noise has good generalization ability to the actual scene. The designed combined features can further improve the classification recognition performance, and the recognition rate of real environmental acoustic events can reach 75%, meeting the requirements of the actual system." @default.
- W2999896480 created "2020-01-23" @default.
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- W2999896480 date "2019-10-01" @default.
- W2999896480 modified "2023-09-26" @default.
- W2999896480 title "Sound Event Recognition Based in Feature Combination with Low SNR" @default.
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- W2999896480 doi "https://doi.org/10.1109/aiam48774.2019.00029" @default.
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