Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Sequence-to-Sequence Baseline for the Voice Conversion Challenge
  2020: Cascading ASR and TTS   This paper presents the sequence-to-sequence (seq2seq) baseline system for
the voice conversion challenge (VCC) 2020. We consider a naive approach for
voice conversion (VC), which is to first transcribe the input speech with an
automatic speech recognition (ASR) model, followed using the transcriptions to
generate the voice of the target with a text-to-speech (TTS) model. We revisit
this method under a sequence-to-sequence (seq2seq) framework by utilizing
ESPnet, an open-source end-to-end speech processing toolkit, and the many
well-configured pretrained models provided by the community. Official
evaluation results show that our system comes out top among the participating
systems in terms of conversion similarity, demonstrating the promising ability
of seq2seq models to convert speaker identity. The implementation is made
open-source at: https://github.com/espnet/espnet/tree/master/egs/vcc20.

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The categories of this paper are: chem-ph
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The categories of this paper are: econ
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The categories of this paper are: cmp-lg
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The categories of this paper are: astro-ph
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The categories of this paper are: acc-phys
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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: ao-sci
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The categories of this paper are: physics
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The categories of this paper are: stat
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The categories of this paper are: gr-qc
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The categories of this paper are: q-alg
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The categories of this paper are: math
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The categories of this paper are: mtrl-th
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th