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• W2890404473 abstract "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." @default.
• W2890404473 created "2018-09-27" @default.
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• W2890404473 date "2018-09-02" @default.
• W2890404473 modified "2023-09-27" @default.
• W2890404473 title "Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations" @default.
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