Work

Improving POS Tagging for Arabic Dialects on Out-of-Domain Texts

Year: 2022

Type: conference-paper

Abstract: We investigate part of speech tagging for four Arabic dialects (Gulf, Levantine, Egyptian, and Maghrebi), in an out-ofdomain setting.More specifically, we look at the effectiveness of 1) upsampling the target dialect in the training data of a joint model, 2) increasing the consistency of the annotations, and 3) using word embeddings pre-trained on a large corpus of dialectal Arabic.We increase the accuracy on average by about 20 percentage points.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/2022.wanlp-1.22

Authors: Noor Abo Mokh, Daniel Dakota, Sandra Kübler

Institution: Indiana University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4385573224

FWCI:

Cites: 39

Cited by:

Related to: 10