INMT-Lite: Accelerating Low-Resource Language Data Collection via Offline Interactive Neural Machine Translation (2024.lrec-main)
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Harshita Diddee, Anurag Shukla, Tanuja Ganu, Vivek Seshadri, Sandipan Dandapat, Monojit Choudhury, Kalika Bali
| Challenge: | Interactive Neural Machine Translation (INMT) systems can be used to promote data collection in several under-resourced languages, but are often not adapted to the deployment constraints native language speakers operate in. |
| Approach: | They propose to use interactive neural machine translation systems to promote data collection in several under-resourced languages by integrating three different modes of Internet-independent deployment and four assistive interfaces suitable for data-sparse languages. |
| Outcome: | The proposed model improves the data generation experience of community members along multiple axes without compromising on the quality of the generated translations. |
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