TY - JOUR AU - Li, Zuchao AU - Wang, Rui AU - Chen, Kehai AU - Utiyama, Masao AU - Sumita, Eiichiro AU - Zhang, Zhuosheng AU - Zhao, Hai PY - 2020/04/03 Y2 - 2024/03/28 TI - Explicit Sentence Compression for Neural Machine Translation JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 34 IS - 05 SE - AAAI Technical Track: Natural Language Processing DO - 10.1609/aaai.v34i05.6347 UR - https://ojs.aaai.org/index.php/AAAI/article/view/6347 SP - 8311-8318 AB - <p>State-of-the-art Transformer-based neural machine translation (NMT) systems still follow a standard encoder-decoder framework, in which source sentence representation can be well done by an encoder with self-attention mechanism. Though Transformer-based encoder may effectively capture general information in its resulting source sentence representation, the backbone information, which stands for the gist of a sentence, is not specifically focused on. In this paper, we propose an explicit sentence compression method to enhance the source sentence representation for NMT. In practice, an explicit sentence compression goal used to learn the backbone information in a sentence. We propose three ways, including backbone source-side fusion, target-side fusion, and both-side fusion, to integrate the compressed sentence into NMT. Our empirical tests on the WMT English-to-French and English-to-German translation tasks show that the proposed sentence compression method significantly improves the translation performances over strong baselines.</p> ER -