Thai Word Segmentation
7 papers with code • 2 benchmarks • 0 datasets
Thai word segmentation
Most implemented papers
LATTE: Lattice ATTentive Encoding for Character-based Word Segmentation
Our model employs the lattice structure to handle segmentation alternatives and utilizes graph neural networks along with an attention mechanism to attentively extract multi-granularity representation from the lattice for complementing character representations.
Multi-Candidate Word Segmentation using Bi-directional LSTM Neural Networks
As a test-bed, the well-known bidirectional long short-term memory (BiLSTM) units are used with eleven contexts in a deep neural network.
AttaCut: A Fast and Accurate Neural Thai Word Segmenter
Word segmentation is a fundamental pre-processing step for Thai Natural Language Processing.
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.