Contextual Neural Model For Translating Bilingual Multi-speaker Conversations
Sameen Maruf, André F. T. Martins, Gholamreza Haffari . Proceedings of the Third Conference on Machine Translation: Research Papers 2018 – 53 citations
[Paper]
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.