Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploring Phoneme-Level Speech Representations for End-to-End Speech
  Translation   Previous work on end-to-end translation from speech has primarily used
frame-level features as speech representations, which creates longer, sparser
sequences than text. We show that a naive method to create compressed
phoneme-like speech representations is far more effective and efficient for
translation than traditional frame-level speech features. Specifically, we
generate phoneme labels for speech frames and average consecutive frames with
the same label to create shorter, higher-level source sequences for
translation. We see improvements of up to 5 BLEU on both our high and low
resource language pairs, with a reduction in training time of 60%. Our
improvements hold across multiple data sizes and two language pairs.

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The categories of this paper are: supr-con
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The categories of this paper are: atom-ph
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The categories of this paper are: math-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: q-bio
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The categories of this paper are: stat
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The categories of this paper are: mtrl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
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The categories of this paper are: solv-int
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The categories of this paper are: q-alg
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-lat