Back to search

Article

Employing a Multilingual Transformer Model for Segmenting Unpunctuated Arabic Text

2022-08-26

Abstract excerpt

Long unpunctuated texts containing complex linguistic sentences are a stumbling block to processing any low-resource languages. Thus, approaches that attempt to segment lengthy texts with no proper punctuation into simple candidate sentences are a vitally important preprocessing task in many hard-to-solve NLP applications. In this paper, we propose (PDTS) a punctuation detection approach for segmenting Arabic text...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
03cee42e-62fe-509a-b715-044a7925118e
DOI
10.20944/preprints202208.0451.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Employing a Multilingual Transformer Model for Segmenting Unpunctuated Arabic TextDOI 10.20944/preprints202208.0451.v1
Select a neighboring publication to make it the new centre.