Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 3D Convolutional Neural Networks for Cross Audio-Visual Matching
  Recognition   Audio-visual recognition (AVR) has been considered as a solution for speech
recognition tasks when the audio is corrupted, as well as a visual recognition
method used for speaker verification in multi-speaker scenarios. The approach
of AVR systems is to leverage the extracted information from one modality to
improve the recognition ability of the other modality by complementing the
missing information. The essential problem is to find the correspondence
between the audio and visual streams, which is the goal of this work. We
propose the use of a coupled 3D Convolutional Neural Network (3D-CNN)
architecture that can map both modalities into a representation space to
evaluate the correspondence of audio-visual streams using the learned
multimodal features. The proposed architecture will incorporate both spatial
and temporal information jointly to effectively find the correlation between
temporal information for different modalities. By using a relatively small
network architecture and much smaller dataset for training, our proposed method
surpasses the performance of the existing similar methods for audio-visual
matching which use 3D CNNs for feature representation. We also demonstrate that
an effective pair selection method can significantly increase the performance.
The proposed method achieves relative improvements over 20% on the Equal Error
Rate (EER) and over 7% on the Average Precision (AP) in comparison to the
state-of-the-art method.

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The categories of this paper are: astro-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-th
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The categories of this paper are: physics
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The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
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The categories of this paper are: comp-gas
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The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: solv-int
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The categories of this paper are: acc-phys
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The categories of this paper are: nlin
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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
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The categories of this paper are: econ