Semi-Supervised NMF-CNN For Sound Event Detection
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For the DCASE 2020 Challenge Task 4, this paper pro-posed a combinative approach using Nonnegative Matrix Factorization (NMF) and Convolutional Neural Network (CNN). The main idea begins with utilizing NMF to ap-proximate strong labels for the weakly labeled data. Sub-sequently, based on the approximated strongly labeled data, two different CNNs are trained using a semi-supervised framework where one CNN is used for clip-level prediction and the other for frame-level prediction. Using this idea, the best model trained can achieve an event-based F1-score of 45.7 models, the event-based F1-score can be increased to 48.6 the base-line model, the proposed model outperforms the baseline model by a margin of over 8
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