Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Honk: A PyTorch Reimplementation of Convolutional Neural Networks for
  Keyword Spotting   We describe Honk, an open-source PyTorch reimplementation of convolutional
neural networks for keyword spotting that are included as examples in
TensorFlow. These models are useful for recognizing "command triggers" in
speech-based interfaces (e.g., "Hey Siri"), which serve as explicit cues for
audio recordings of utterances that are sent to the cloud for full speech
recognition. Evaluation on Google's recently released Speech Commands Dataset
shows that our reimplementation is comparable in accuracy and provides a
starting point for future work on the keyword spotting task.

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The categories of this paper are: chao-dyn
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The categories of this paper are: nlin
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The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
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The categories of this paper are: hep-th
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The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
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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: alg-geom
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The categories of this paper are: q-bio
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga