Sound Event Detection in Domestic Environments using Dense Recurrent Neural Network
In this paper, we introduce our sound events detection system using a mean-teacher model with convolutional recurrent neural network (CRNN) for DCASE 2020 Task4, which include residual convolutional block and dense recurrent neural network (DRNN) block. To improve the performance of system, we propose to use various methods such as multi-scale input layer, data augmentation, median window filters and model fusion. By combining those method, our system achieves 15% improvement on macro-averaged F-score on the development set, as compared to the baseline.
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