Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning

• URL: http://arxiv.org/abs/2002.04306v2
• Date: Mon, 25 Jan 2021 05:48:24 GMT
• Title: Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning
• Authors: Philip Arthur, Trevor Cohn, Gholamreza Haffari
• Abstract summary: We present an approach to efficiently learn a simultaneous translation model with coupled programmer-interpreter policies. Experiments on six language-pairs show our method outperforms strong baselines in terms of translation quality.
• Score: 85.70547744787
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a novel approach to efficiently learn a simultaneous translation model with coupled programmer-interpreter policies. First, wepresent an algorithmic oracle to produce oracle READ/WRITE actions for training bilingual sentence-pairs using the notion of word alignments. This oracle actions are designed to capture enough information from the partial input before writing the output. Next, we perform a coupled scheduled sampling to effectively mitigate the exposure bias when learning both policies jointly with imitation learning. Experiments on six language-pairs show our method outperforms strong baselines in terms of translation quality while keeping the translation delay low.

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