Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generative Spoken Dialogue Language Modeling   We introduce dGSLM, the first "textless" model able to generate audio samples
of naturalistic spoken dialogues. It uses recent work on unsupervised spoken
unit discovery coupled with a dual-tower transformer architecture with
cross-attention trained on 2000 hours of two-channel raw conversational audio
(Fisher dataset) without any text or labels. It is able to generate speech,
laughter and other paralinguistic signals in the two channels simultaneously
and reproduces naturalistic turn taking. Generation samples can be found at:
https://speechbot.github.io/dgslm.

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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: hep-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-lat
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The categories of this paper are: gr-qc
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-th
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The categories of this paper are: stat
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The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: math
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The categories of this paper are: patt-sol
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The categories of this paper are: nlin