Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contextual Neural Model for Translating Bilingual Multi-Speaker
  Conversations   Recent works in neural machine translation have begun to explore document
translation. However, translating online multi-speaker conversations is still
an open problem. In this work, we propose the task of translating Bilingual
Multi-Speaker Conversations, and explore neural architectures which exploit
both source and target-side conversation histories for this task. To initiate
an evaluation for this task, we introduce datasets extracted from Europarl v7
and OpenSubtitles2016. Our experiments on four language-pairs confirm the
significance of leveraging conversation history, both in terms of BLEU and
manual evaluation.

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The categories of this paper are: econ
29
The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
19
The categories of this paper are: eess
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The categories of this paper are: nlin
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: cmp-lg
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The categories of this paper are: gr-qc
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: q-alg
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The categories of this paper are: astro-ph
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The categories of this paper are: quant-ph