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TDNN: A Two-stage Deep Neural Network for Prompt-independent Automated Essay Scoring

Cancan Jin, Ben He, Kai Hui, Le Sun
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
To close this gap, a two-stage deep neural network (TDNN) is proposed.  ...  Existing automated essay scoring (AES) models rely on rated essays for the target prompt as training data.  ...  Acknowledgments This work is supported in part by the National Natural Science Foundation of China (61472391), and the Project of Beijing Advanced Innovation Center for Language Resources (451122512).  ... 
doi:10.18653/v1/p18-1100 dblp:conf/acl/SunHHJ18 fatcat:jfm7ssqakrcpdjnlcl7lvupmuu

Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring [article]

Haoran Zhang, Diane Litman
2020 arXiv   pre-print
While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision.  ...  However, a neural AES typically does not provide useful feature representations for supporting AWE.  ...  Acknowledgments We would like to show our appreciation to every member of the RTA group for sharing their pearls of wisdom with us.  ... 
arXiv:2008.01809v1 fatcat:hcu3uzutfjbzfpqcwnthliz6va

Automated Evaluation of Writing – 50 Years and Counting

Beata Beigman Klebanov, Nitin Madnani
2020 Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics   unpublished
See Ke and Ng (2019) for a recent review. 2 https://pearsonpte.com/the-test/ about-our-scores/how-is-the-test-scored/ 3 https://www.ets.org/gre/revised_general/ scores/how/ 4 https://www.ets.org/toefl/  ...  In this theme paper, we reflect on the progress of Automated Writing Evaluation (AWE), using Ellis Page's seminal 1966 paper to frame the presentation.  ...  Acknowledgements We would like to thank our colleagues Anastassia Loukina, Jill Burstein, Aoife Cahill, and Isaac Bejar, as well as ACL reviewers and area chair, for their thoughtful comments on earlier  ... 
doi:10.18653/v1/2020.acl-main.697 fatcat:6kxnj2a5cbhhxhdadvbsua5j24

Deep Learning for Automatic Assessment and Feedback of Spoken English

Konstantinos Kyriakopoulos, Apollo-University Of Cambridge Repository, Mark Gales
2022
Growing global demand for learning a second language (L2), particularly English, has led to considerable interest in automatic spoken language assessment, whether for use in computerassisted language learning  ...  Conversely, holistic scores are available for various standard assessment tasks such as Linguaskill.  ...  The first two are two-stage baselines, specifically a feed-forward neural network trained on f 0 statistics computed across all data from each speaker (DNN) and a feed-forward neural network trained on  ... 
doi:10.17863/cam.82947 fatcat:icc75rjxwjegpeuegv6oylatoy

AIUCD 2021 - Book of Extended Abstracts

Federico Boschetti, Angelo Mario Del Grosso, Enrica Salvatori
2021
Questo volume raccoglie gli abstract estesi e sottoposti a review per la conferenza di AIUCD2021 tenutasi in forma virtuale a Pisa.  ...  ACKNOWLEDGEMENTS The authors want to thank Yoann Moranville (DARIAH), Paula Forbes (Abertay University), and Mélanie Bunuel (Huma-num -CNRS) for their contributions to this paper.  ...  This accomplished using a neural network. In our work, we analysed two solutions.  ... 
doi:10.6092/unibo/amsacta/6712 fatcat:672tcvwzsvhixnic2cnjkfw72e