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EURASIP Journal on Audio, Speech, and Music Processing
Fig. 1 | EURASIP Journal on Audio, Speech, and Music Processing

Fig. 1

From: Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks

Fig. 1

An overview of our deep learning framework composed of a pre-trained CNN (here exemplified with VGG16) used as feature extractor and a CRNN block. First, the spectrograms are created from the audio recordings. Afterwards, using the pre-trained CNN and our CRNN, block predictions are obtained. In the last step, a decision-level fusion is conducted to get the final predictions. For a detailed account on the framework, refer to Section 3

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