TY - GEN
T1 - Diamonds in the rough
T2 - 12th International Conference on Natural Language Generation, INLG 2019
AU - Ito, Takumi
AU - Kuribayashi, Tatsuki
AU - Kobayashi, Hayato
AU - Brassard, Ana
AU - Hagiwara, Masato
AU - Suzuki, Jun
AU - Inui, Kentaro
N1 - Publisher Copyright:
© 2019 Association for Computational Linguistics
PY - 2019
Y1 - 2019
N2 - The writing process consists of several stages such as drafting, revising, editing, and proofreading. Studies on writing assistance, such as grammatical error correction (GEC), have mainly focused on sentence editing and proofreading, where surface-level issues such as typographical, spelling, or grammatical errors should be corrected. We broaden this focus to include the earlier revising stage, where sentences require adjustment to the information included or major rewriting and propose Sentence-level Revision (SentRev) as a new writing assistance task. Well-performing systems in this task can help inexperienced authors by producing fluent, complete sentences given their rough, incomplete drafts. We build a new freely available crowdsourced evaluation dataset consisting of incomplete sentences authored by non-native writers paired with their final versions extracted from published academic papers for developing and evaluating SentRev models. We also establish baseline performance on SentRev using our newly built evaluation dataset.
AB - The writing process consists of several stages such as drafting, revising, editing, and proofreading. Studies on writing assistance, such as grammatical error correction (GEC), have mainly focused on sentence editing and proofreading, where surface-level issues such as typographical, spelling, or grammatical errors should be corrected. We broaden this focus to include the earlier revising stage, where sentences require adjustment to the information included or major rewriting and propose Sentence-level Revision (SentRev) as a new writing assistance task. Well-performing systems in this task can help inexperienced authors by producing fluent, complete sentences given their rough, incomplete drafts. We build a new freely available crowdsourced evaluation dataset consisting of incomplete sentences authored by non-native writers paired with their final versions extracted from published academic papers for developing and evaluating SentRev models. We also establish baseline performance on SentRev using our newly built evaluation dataset.
UR - http://www.scopus.com/inward/record.url?scp=85087163024&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087163024&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85087163024
T3 - INLG 2019 - 12th International Conference on Natural Language Generation, Proceedings of the Conference
SP - 40
EP - 53
BT - INLG 2019 - 12th International Conference on Natural Language Generation, Proceedings of the Conference
PB - Association for Computational Linguistics (ACL)
Y2 - 29 October 2019 through 1 November 2019
ER -