Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Recent Progresses in Deep Learning based Acoustic Models (Updated)   In this paper, we summarize recent progresses made in deep learning based
acoustic models and the motivation and insights behind the surveyed techniques.
We first discuss acoustic models that can effectively exploit variable-length
contextual information, such as recurrent neural networks (RNNs), convolutional
neural networks (CNNs), and their various combination with other models. We
then describe acoustic models that are optimized end-to-end with emphasis on
feature representations learned jointly with rest of the system, the
connectionist temporal classification (CTC) criterion, and the attention-based
sequence-to-sequence model. We further illustrate robustness issues in speech
recognition systems, and discuss acoustic model adaptation, speech enhancement
and separation, and robust training strategies. We also cover modeling
techniques that lead to more efficient decoding and discuss possible future
directions in acoustic model research.

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The categories of this paper are: mtrl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-lat
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The categories of this paper are: comp-gas
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: funct-an
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The categories of this paper are: hep-th
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The categories of this paper are: alg-geom
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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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: q-fin
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The categories of this paper are: cmp-lg