Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multistream neural architectures for cued-speech recognition using a
  pre-trained visual feature extractor and constrained CTC decoding   This paper proposes a simple and effective approach for automatic recognition
of Cued Speech (CS), a visual communication tool that helps people with hearing
impairment to understand spoken language with the help of hand gestures that
can uniquely identify the uttered phonemes in complement to lipreading. The
proposed approach is based on a pre-trained hand and lips tracker used for
visual feature extraction and a phonetic decoder based on a multistream
recurrent neural network trained with connectionist temporal classification
loss and combined with a pronunciation lexicon. The proposed system is
evaluated on an updated version of the French CS dataset CSF18 for which the
phonetic transcription has been manually checked and corrected. With a decoding
accuracy at the phonetic level of 70.88%, the proposed system outperforms our
previous CNN-HMM decoder and competes with more complex baselines.

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The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: hep-th
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
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The categories of this paper are: stat
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The categories of this paper are: funct-an
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-ex