• Corpus ID: 214797192

ATTENTION-BASED CONVOLUTIONAL NEURAL NETWORK FOR AUDIO EVENT CLASSIFICATION WITH FEATURE TRANSFER LEARNING

@inproceedings{Chen2018ATTENTIONBASEDCN,
  title={ATTENTION-BASED CONVOLUTIONAL NEURAL NETWORK FOR AUDIO EVENT CLASSIFICATION WITH FEATURE TRANSFER LEARNING},
  author={Tianxiang Chen and Udit Gupta},
  year={2018}
}
Audio event classification is an urgent Content based Information Retrieval (CBIR) unsolved problem with numerous applications that it can benefit. This paper is explaining Pindrop’s submission to the ”Making Sense of Sound” challenge. In this submission we address the challenge of classifying audio excerpts based on their origin by using Convolutional Neural Networks with feature transfer learning. We use pretrained VGGish network to extract feature embeddings. Our results show a remarkable… 
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PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
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This paper proposes pretrained audio neural networks (PANNs) trained on the large-scale AudioSet dataset, and investigates the performance and computational complexity of PANNs modeled by a variety of convolutional neural networks.

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