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Word-level Morpheme segmentation using Transformer neural network

2022-07-01 · NAACL (SIGMORPHON) 2022 7 · Tsolmon Zundi, Chinbat Avaajargal

This paper presents the submission of team NUM DI to the SIGMORPHON 2022 Task on Morpheme Segmentation Part 1, word-level morpheme segmentation. We explore the transformer neural network approach to the shared task. We develop monolingual models for world-level morpheme segmentation and focus on improving the model by using various training strategies to improve accuracy and generalization across languages.

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Segmentation

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