Thai Word Segmentation

LATTE: Lattice ATTentive Encoding for Character-based Word Segmentation

A character sequence comprises at least one or more segmentation alternatives. This can be considered segmentation ambiguity and may weaken segmentation performance in word segmentation. Proper handling of such ambiguity…

Character-based Thai Word Segmentation with Multiple Attentions

Character-based word-segmentation models have been extensively applied to agglutinative languages, including Thai, due to their high performance. These models estimate word boundaries from a character sequence. However, …

Handling Cross- and Out-of-Domain Samples in Thai Word Segmentation

Syllable-based Neural Thai Word Segmentation

Word segmentation is a challenging pre-processing step for Thai Natural Language Processing due to the lack of explicit word boundaries.The previous systems rely on powerful neural network architecture alone and ignore l…

Domain Adaptation of Thai Word Segmentation Models using Stacked Ensemble

Like many Natural Language Processing tasks, Thai word segmentation is domain-dependent. Researchers have been relying on transfer learning to adapt an existing model to a new domain. However, this approach is inapplicab…

ThaiLMCut: Unsupervised Pretraining for Thai Word Segmentation

We propose ThaiLMCut, a semi-supervised approach for Thai word segmentation which utilizes a bi-directional character language model (LM) as a way to leverage useful linguistic knowledge from unlabeled data. After the la…