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Using exemplar responses for training and evaluating automated speech scoring systems.

, , , and . BEA@NAACL-HLT, page 1-12. Association for Computational Linguistics, (2018)

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Expert and crowdsourced annotation of pronunciation errors for automatic scoring systems., , , , and . INTERSPEECH, page 2809-2813. ISCA, (2015)Exploiting Structured Error to Improve Automated Scoring of Oral Reading Fluency., and . AIED (2), volume 12749 of Lecture Notes in Computer Science, page 76-81. Springer, (2021)Building Better Open-Source Tools to Support Fairness in Automated Scoring., , , , and . EthNLP@EACL, page 41-52. Association for Computational Linguistics, (2017)Automated scoring across different modalities., and . BEA@NAACL-HLT, page 130-135. The Association for Computer Linguistics, (2016)A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring., , and . BEA@EMNLP, page 457-467. Association for Computational Linguistics, (2017)Automatic Detection of Word-Level Reading Errors in Non-native English Speech Based on ASR Output., , , , , , and . ISCSLP, page 1-5. IEEE, (2021)A Good Start is Half the Battle Won: Unsupervised Pre-training for Low Resource Children's Speech Recognition for an Interactive Reading Companion., , , , and . AIED (1), volume 12748 of Lecture Notes in Computer Science, page 306-317. Springer, (2021)Atypical Inputs in Educational Applications., , , , , and . NAACL-HLT (3), page 60-67. Association for Computational Linguistics, (2018)Acoustic model of stress in standard Greek and Greek dialects.. ExLing, page 149-152. ISCA, (2008)Continuous fluency tracking and the challenges of varying text complexity., , , and . BEA@EMNLP, page 22-32. Association for Computational Linguistics, (2017)