{"title":"基于编辑操作预测的可控文本简化的词法约束解码","authors":"Tatsuya Zetsu, Tomoyuki Kajiwara, Yuki Arase","doi":"10.18653/v1/2022.tsar-1.13","DOIUrl":null,"url":null,"abstract":"Controllable text simplification assists language learners by automatically rewriting complex sentences into simpler forms of a target level. However, existing methods tend to perform conservative edits that keep complex words intact. To address this problem, we employ lexically constrained decoding to encourage rewriting. Specifically, the proposed method predicts edit operations conditioned to a target level and creates positive/negative constraints for words that should/should not appear in an output sentence. The experimental results confirm that our method significantly outperforms previous methods and demonstrates a new state-of-the-art performance.","PeriodicalId":247582,"journal":{"name":"Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Lexically Constrained Decoding with Edit Operation Prediction for Controllable Text Simplification\",\"authors\":\"Tatsuya Zetsu, Tomoyuki Kajiwara, Yuki Arase\",\"doi\":\"10.18653/v1/2022.tsar-1.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Controllable text simplification assists language learners by automatically rewriting complex sentences into simpler forms of a target level. However, existing methods tend to perform conservative edits that keep complex words intact. To address this problem, we employ lexically constrained decoding to encourage rewriting. Specifically, the proposed method predicts edit operations conditioned to a target level and creates positive/negative constraints for words that should/should not appear in an output sentence. The experimental results confirm that our method significantly outperforms previous methods and demonstrates a new state-of-the-art performance.\",\"PeriodicalId\":247582,\"journal\":{\"name\":\"Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/2022.tsar-1.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/2022.tsar-1.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lexically Constrained Decoding with Edit Operation Prediction for Controllable Text Simplification
Controllable text simplification assists language learners by automatically rewriting complex sentences into simpler forms of a target level. However, existing methods tend to perform conservative edits that keep complex words intact. To address this problem, we employ lexically constrained decoding to encourage rewriting. Specifically, the proposed method predicts edit operations conditioned to a target level and creates positive/negative constraints for words that should/should not appear in an output sentence. The experimental results confirm that our method significantly outperforms previous methods and demonstrates a new state-of-the-art performance.