Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DCASE 2018 Challenge: Solution for Task 5   To address Task 5 in the Detection and Classification of Acoustic Scenes and
Events (DCASE) 2018 challenge, in this paper, we propose an ensemble learning
system. The proposed system consists of three different models, based on
convolutional neural network and long short memory recurrent neural network.
With extracted features such as spectrogram and mel-frequency cepstrum
coefficients from different channels, the proposed system can classify
different domestic activities effectively. Experimental results obtained from
the provided development dataset show that good performance with F1-score of
92.19% can be achieved. Compared with the baseline system, our proposed system
significantly improves the performance of F1-score by 7.69%.

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The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
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The categories of this paper are: chem-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th