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• W2893186003 abstract "Whilst the focus of Machine Translation (MT) has for a long time been the translation of planned, written texts, more and more research is being dedicated to translating speech-like texts (informal or spontaneous discourse or dialogue). To achieve high quality and natural translation of speech-like texts, the integration of context is needed, whether it is extra-linguistic (speaker identity, the interaction between speaker and interlocutor) or linguistic (coreference and stylistic phenomena linked to the spontaneous and informal nature of the texts). However, the integration of contextual information in MT systems remains limited in most current systems. In this paper, we present and critique three experiments for the integration of context into a MT system, each focusing on a different type of context and exploiting a different method: adaptation to speaker gender, cross-lingual pronoun prediction and the generation of tag questions from French into English." @default.
• W2893186003 created "2018-10-05" @default.
• W2893186003 creator A5046431394 @default.
• W2893186003 date "2017-06-26" @default.
• W2893186003 modified "2023-10-16" @default.
• W2893186003 title "Machine Translation of Speech-Like Texts: Strategies for the Inclusion of Context" @default.
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• W2893186003 hasPublicationYear "2017" @default.
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