%I Association for Computational Linguistics %S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) %T Modeling Dual Read/Write Paths for Simultaneous Machine Translation Experiments on En-Vi and De-En tasks show that our method can outperform strong baselines under all latency. As a result, the two SiMT models can be optimized jointly by forcing their read/write paths to satisfy the mapping. According to duality constraints, the read/write path in source-to-target and target-to-source SiMT models can be mapped to each other. In this paper, we propose a method of dual-path SiMT which introduces duality constraints to direct the read/write path. Although the read/write path is essential to SiMT performance, no direct supervision is given to the path in the existing methods. Simultaneous machine translation (SiMT) outputs translation while reading source sentence and hence requires a policy to decide whether to wait for the next source word (READ) or generate a target word (WRITE), the actions of which form a read/write path. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)Īssociation for Computational Linguistics Modeling Dual Read/Write Paths for Simultaneous Machine Translation Experiments on En-Vi and De-En tasks show that our method can outperform strong baselines under all latency.", ![]() Publisher = "Association for Computational Linguistics",Ībstract = "Simultaneous machine translation (SiMT) outputs translation while reading source sentence and hence requires a policy to decide whether to wait for the next source word (READ) or generate a target word (WRITE), the actions of which form a read/write path. Cite (Informal): Modeling Dual Read/Write Paths for Simultaneous Machine Translation (Zhang & Feng, ACL 2022) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: Code = "Modeling Dual Read/Write Paths for Simultaneous Machine Translation",īooktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", Association for Computational Linguistics. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2461–2477, Dublin, Ireland. Modeling Dual Read/Write Paths for Simultaneous Machine Translation. Anthology ID: 2022.acl-long.176 Volume: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) Month: May Year: 2022 Address: Dublin, Ireland Venue: ACL SIG: Publisher: Association for Computational Linguistics Note: Pages: 2461–2477 Language: URL: DOI: 10.18653/v1/2022.acl-long.176 Bibkey: zhang-feng-2022-modeling Cite (ACL): Shaolei Zhang and Yang Feng. ![]() See our RFID Module & Tag Compatibility Chart here.Abstract Simultaneous machine translation (SiMT) outputs translation while reading source sentence and hence requires a policy to decide whether to wait for the next source word (READ) or generate a target word (WRITE), the actions of which form a read/write path. The RFID Read/Write Module can be used in a wide variety of hobbyist and commercial applications, including access control, user identification, robotics navigation, inventory tracking, payment systems, car immobilization, and manufacturing automation. The RFID transponder tags provide a unique serial number and can store up to 116 bytes of user data, which can be password protected to allow only authorized access. Designed in cooperation with Grand Idea Studio, the Parallax Radio Frequency Identification (RFID) Read/Write Module provides a low-cost solution to read and write passive RFID transponder tags up to 3 inches away.
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