title: Smart Word Suggestions for Writing Assistance
summary: Enhancing word usage is a desired feature for writing assistance. To further
  advance research in this area, this paper introduces "Smart Word Suggestions"
  (SWS) task and benchmark. Unlike other works, SWS emphasizes end-to-end
  evaluation and presents a more realistic writing assistance scenario. This task
  involves identifying words or phrases that require improvement and providing
  substitution suggestions. The benchmark includes human-labeled data for
  testing, a large distantly supervised dataset for training, and the framework
  for evaluation. The test data includes 1,000 sentences written by English
  learners, accompanied by over 16,000 substitution suggestions annotated by 10
  native speakers. The training dataset comprises over 3.7 million sentences and
  12.7 million suggestions generated through rules. Our experiments with seven
  baselines demonstrate that SWS is a challenging task. Based on experimental
  analysis, we suggest potential directions for future research on SWS. The
  dataset and related codes is available at
  https://github.com/microsoft/SmartWordSuggestions.
paper_authors._id: 646596f53732b3510ecc2b81
paper_authors.name: Chenshuo Wang
paper_authors._id: 646596f53732b3510ecc2b82
paper_authors.name: Shaoguang Mao
paper_authors._id: 646596f53732b3510ecc2b83
paper_authors.name: Tao Ge
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-02-05T10:51:12.197Z
paper_authors._id: 64ab5db78a1a9187c215f45a
paper_authors.avatarUrl: /avatars/17add4cd02e183f9b9d4feb7b6c27c21.svg
paper_authors.fullname: Tao Ge
paper_authors.type: user
paper_authors.user: sggetao
paper_authors._id: 646596f53732b3510ecc2b84
paper_authors.name: Wenshan Wu
paper_authors._id: 646596f53732b3510ecc2b85
paper_authors.name: Xun Wang
paper_authors._id: 646596f53732b3510ecc2b86
paper_authors.name: Yan Xia
paper_authors._id: 646596f53732b3510ecc2b87
paper_authors.name: Jonathan Tien
paper_authors._id: 646596f53732b3510ecc2b88
paper_authors.name: Dongyan Zhao
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-06-02T15:03:37.320Z
paper_authors._id: 629ee8171fec321a2d3c458d
paper_authors.avatarUrl: /avatars/a8ae78b193ba2a43c6e36e185e0ef2b9.svg
paper_authors.fullname: Zhaodong Yan
paper_authors.type: user
paper_authors.user: Anhforth
paper_title: Smart Word Suggestions for Writing Assistance
paper_summary: Enhancing word usage is a desired feature for writing assistance. To further
  advance research in this area, this paper introduces "Smart Word Suggestions"
  (SWS) task and benchmark. Unlike other works, SWS emphasizes end-to-end
  evaluation and presents a more realistic writing assistance scenario. This task
  involves identifying words or phrases that require improvement and providing
  substitution suggestions. The benchmark includes human-labeled data for
  testing, a large distantly supervised dataset for training, and the framework
  for evaluation. The test data includes 1,000 sentences written by English
  learners, accompanied by over 16,000 substitution suggestions annotated by 10
  native speakers. The training dataset comprises over 3.7 million sentences and
  12.7 million suggestions generated through rules. Our experiments with seven
  baselines demonstrate that SWS is a challenging task. Based on experimental
  analysis, we suggest potential directions for future research on SWS. The
  dataset and related codes is available at
  https://github.com/microsoft/SmartWordSuggestions.
paper_ai_summary: The paper introduces the Smart Word Suggestions (SWS) task and benchmark, focusing on end-to-end evaluation and realistic writing assistance scenarios through human-labeled and rules-generated datasets.
paper_ai_keywords: Smart Word Suggestions SWS end-to-end evaluation human-labeled data distantly supervised dataset substitution suggestions