Papers by Suteera Seeha
ThaiLMCut: Unsupervised Pretraining for Thai Word Segmentation (2020.lrec-1)
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Suteera Seeha, Ivan Bilan, Liliana Mamani Sanchez, Johannes Huber, Michael Matuschek, Hinrich Schütze
| Challenge: | ThaiLMCut is a semi-supervised word segmentation model for word segmenting in Thai . it uses a bi-directional character language model to leverage useful linguistic knowledge from unlabeled data. |
| Approach: | They propose a semi-supervised approach to Thai word segmentation using a character language model. |
| Outcome: | The proposed approach outperforms state-of-the-art models on the benchmark InterBEST2009. |