Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A multi-view approach for Mandarin non-native mispronunciation
  verification   Traditionally, the performance of non-native mispronunciation verification
systems relied on effective phone-level labelling of non-native corpora. In
this study, a multi-view approach is proposed to incorporate discriminative
feature representations which requires less annotation for non-native
mispronunciation verification of Mandarin. Here, models are jointly learned to
embed acoustic sequence and multi-source information for speech attributes and
bottleneck features. Bidirectional LSTM embedding models with contrastive
losses are used to map acoustic sequences and multi-source information into
fixed-dimensional embeddings. The distance between acoustic embeddings is taken
as the similarity between phones. Accordingly, examples of mispronounced phones
are expected to have a small similarity score with their canonical
pronunciations. The approach shows improvement over GOP-based approach by
+11.23% and single-view approach by +1.47% in diagnostic accuracy for a
mispronunciation verification task.

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The categories of this paper are: comp-gas
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The categories of this paper are: plasm-ph
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The categories of this paper are: adap-org
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The categories of this paper are: astro-ph
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The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an
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The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-ex
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The categories of this paper are: supr-con
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The categories of this paper are: quant-ph