Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mandarin-English Code-switching Speech Recognition with Self-supervised
  Speech Representation Models   Code-switching (CS) is common in daily conversations where more than one
language is used within a sentence. The difficulties of CS speech recognition
lie in alternating languages and the lack of transcribed data. Therefore, this
paper uses the recently successful self-supervised learning (SSL) methods to
leverage many unlabeled speech data without CS. We show that hidden
representations of SSL models offer frame-level language identity even if the
models are trained with English speech only. Jointly training CTC and language
identification modules with self-supervised speech representations improves CS
speech recognition performance. Furthermore, using multilingual speech data for
pre-training obtains the best CS speech recognition.

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The categories of this paper are: plasm-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: dg-ga
3
The categories of this paper are: physics
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The categories of this paper are: alg-geom
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The categories of this paper are: math-ph
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The categories of this paper are: q-fin
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The categories of this paper are: hep-ex
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The categories of this paper are: econ
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The categories of this paper are: stat
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The categories of this paper are: nlin
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The categories of this paper are: supr-con
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The categories of this paper are: q-alg
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: mtrl-th