Papers with word segmentation task

2 papers
Building a Word Segmenter for Sanskrit Overnight (L18-1)

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Challenge: Sanskrit word segmentation is challenging due to the issue of Sandhi . digitisation efforts have made the manuscripts available in the public domain .
Approach: They propose a deep sequence to sequence model that takes only the sandhied string as input and predicts the unsandhized string.
Outcome: The proposed model improves on the current state of the art by 16.79% . the system can be trained "overnight" and be used for production .
ThaiLMCut: Unsupervised Pretraining for Thai Word Segmentation (2020.lrec-1)

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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.

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