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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention

The proposed model consists of three subsystems: Feature Extractor, Attention-based Classification Model, and Lexical Stress Error Detector.

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Cite this as

Daniel Korzekwa, Roberto Barra-Chicote, Szymon Zaporowski, Grzegorz Beringer, Jaime Lorenzo-Trueba, Alicja Serafinowicz, Jasha Droppo, Thomas Drugman, Bozena Kostek (2024). Dataset: Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention. https://doi.org/10.57702/7t9bdzpa

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Additional Info

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2012.14788
Author Daniel Korzekwa
More Authors
Roberto Barra-Chicote
Szymon Zaporowski
Grzegorz Beringer
Jaime Lorenzo-Trueba
Alicja Serafinowicz
Jasha Droppo
Thomas Drugman
Bozena Kostek
Homepage https://arxiv.org/abs/2106.05444