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- W4293791330 abstract "Musical instrument recognition is an essential task in the domain of music information retrieval. So far, most existing research are focused on western instruments. In this research, we turn to Chinese national instruments recognition. First, a dataset containing 30 Chinese national instruments is created. Then, a well-designed end-to-end Convolutional Recurrent Neural Network is proposed. Moreover, we combine instrument recognition with instrument timbre space regression using a multitask learning approach to improve performances of both tasks. We conduct experiments in instrument recognition and timbre space regression to evaluate our model and multitask learning approach. Experimental results show that our proposed model outperforms previous algorithms, and the multitask approach can further improve the results." @default.
- W4293791330 created "2022-08-31" @default.
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- W4293791330 date "2022-09-01" @default.
- W4293791330 modified "2023-10-14" @default.
- W4293791330 title "A Multitask Learning Approach for Chinese National Instruments Recognition and Timbre Space Regression" @default.
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- W4293791330 doi "https://doi.org/10.1007/978-981-19-4703-2_1" @default.
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