BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation (2022.acl-long)
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| Challenge: | Existing IMT systems relying on lexical constrained decoding (LCD) are limited in translation efficiency and quality due to LCD. |
| Approach: | They propose a novel interactive neural machine translation system that uses lexical constraints to decode missing words in a manually revised translation. |
| Outcome: | The proposed system performs significantly better and faster than state-of-the-art IMT on three translation tasks. |
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