Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Audio Visual Emotion Recognition with Temporal Alignment and Perception
  Attention   This paper focuses on two key problems for audio-visual emotion recognition
in the video. One is the audio and visual streams temporal alignment for
feature level fusion. The other one is locating and re-weighting the perception
attentions in the whole audio-visual stream for better recognition. The Long
Short Term Memory Recurrent Neural Network (LSTM-RNN) is employed as the main
classification architecture. Firstly, soft attention mechanism aligns the audio
and visual streams. Secondly, seven emotion embedding vectors, which are
corresponding to each classification emotion type, are added to locate the
perception attentions. The locating and re-weighting process is also based on
the soft attention mechanism. The experiment results on EmotiW2015 dataset and
the qualitative analysis show the efficiency of the proposed two techniques.

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The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
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The categories of this paper are: stat
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: nlin
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The categories of this paper are: adap-org
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The categories of this paper are: physics
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an