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The many dimensions of algorithmic fairness in educational applications., , и . BEA@ACL, стр. 1-10. Association for Computational Linguistics, (2019)Feature selection for automated speech scoring., , , и . BEA@NAACL-HLT, стр. 12-19. The Association for Computer Linguistics, (2015)Using exemplar responses for training and evaluating automated speech scoring systems., , , и . BEA@NAACL-HLT, стр. 1-12. Association for Computational Linguistics, (2018)Using Chunk Based Partial Parsing of Spontaneous Speech in Unrestricted Domains for Reducing Word Error Rate in Speech Recognition., и . COLING-ACL, стр. 1453-1459. Morgan Kaufmann Publishers / ACL, (1998)Discourse Annotation of Non-native Spontaneous Spoken Responses Using the Rhetorical Structure Theory Framework., , , , и . ACL (2), стр. 263-268. Association for Computational Linguistics, (2017)Do Face Masks Introduce Bias in Speech Technologies? The Case of Automated Scoring of Speaking Proficiency., , , , и . INTERSPEECH, стр. 1942-1946. ISCA, (2020)What did they actually say? agreement and disagreement among transcribers of non-native spontaneous speech responses in an English proficiency test.. SLaTE, стр. 25-28. ISCA, (2009)Modeling Discourse Coherence for the Automated Scoring of Spontaneous Spoken Responses., , , и . SLaTE, стр. 132-137. ISCA, (2017)Exploring Content Features for Automated Speech Scoring., , и . HLT-NAACL, стр. 103-111. The Association for Computational Linguistics, (2012)Efficient Optimization for Bilingual Sentence Alignment Based on Linear Regression., , , и . ParallelTexts@NAACL-HLT, (2003)