Papers with word segmentation system

2 papers
Urdu Word Segmentation using Conditional Random Fields (CRFs) (C18-1)

Copied to clipboard

Challenge: Urdu is amongst languages for which word segmentation is a complex task as it exhibits space omission and space insertion issues.
Approach: They propose a word segmentation system for Urdu which uses a Conditional Random Field sequence modeler with orthographic, linguistic and morphological features.
Outcome: The proposed system achieves an F1 score for word boundary identification and 0.85 for sub-word boundary identification tasks.
Syllable-based Neural Thai Word Segmentation (2020.coling-main)

Copied to clipboard

Challenge: Word segmentation is a challenging pre-processing step for Thai Natural Language Processing due to the lack of explicit word boundaries.
Approach: They propose a neural Thai word segmenter that uses syllable embeddings to capture linguistic constraints and dilated CNN filters to capture the environment of each character.
Outcome: The proposed system outperforms the previous state-of-the-art system on both in-domain and out-domain datasets.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations