運用集成式多通道類神經網路於科技英文寫作評估

Yuh Shyang Wang, Lung Hao Lee, Bo Lin Lin, Liang Chih Yu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

A huge number of scientific papers have been authored by non-native English speakers. There is a large demand for effective computer-based writing tools to help writers composing scientific articles. The Automated Evaluation of Scientific Writing (AESW) shared task seeks to promote the use of NLP tools for improving the quality of scientific writing in English by predicting whether a given sentence needs language editing or not. In this study, we propose an ensemble multi-channel BiLSTM-CNN model based on a series of experiments in comparing the number of channels, network architectures, and ensemble size. Our model achieved an F1 score of 63.28 outperforms participating systems in the AESW 2016 task.

貢獻的翻譯標題Scientific Writing Evaluation Using Ensemble Multi-channel Neural Networks
原文繁體中文
主出版物標題ROCLING 2020 - 32nd Conference on Computational Linguistics and Speech Processing
編輯Jenq-Haur Wang, Ying-Hui Lai, Lung-Hao Lee, Kuan-Yu Chen, Hung-Yi Lee, Chi-Chun Lee, Syu-Siang Wang, Hen-Hsen Huang, Chuan-Ming Liu
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面359-371
頁數13
ISBN(電子)9789869576932
出版狀態已出版 - 2020
事件32nd Conference on Computational Linguistics and Speech Processing, ROCLING 2020 - Taipei, Taiwan
持續時間: 24 9月 202026 9月 2020

出版系列

名字ROCLING 2020 - 32nd Conference on Computational Linguistics and Speech Processing

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???event.eventtypes.event.conference???32nd Conference on Computational Linguistics and Speech Processing, ROCLING 2020
國家/地區Taiwan
城市Taipei
期間24/09/2026/09/20

Keywords

  • Automated Writing Evaluation
  • Ensemble Learning
  • Multi-channel Neural Networks
  • Scientific English

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