Work

ARBML: Democratizing Arabic Natural Language Processing Tools

Year: 2020

Type: conference-paper

Abstract: Automating natural language understanding is a lifelong quest addressed for decades. With the help of advances in machine learning and particularly, deep learning, we are able to produce state of the art models that can imitate human interactions with languages. Unfortunately, these advances are controlled by the availability of language resources. Arabic advances in this field , although it has a great potential, are still limited. This is apparent in both research and development. In this paper, we showcase some NLP models we trained for Arabic. We also present our methodology and pipeline to build such models from data collection, data preprocessing, tokenization and model deployment. These tools help in the advancement of the field and provide a systematic approach for extending NLP tools to many languages.

Source: Workshop for NLP Open Source Software (NLP-OSS)

DOI: 10.18653/v1/2020.nlposs-1.2

Authors: Zaid Alyafeai, Maged S. Al-Shaibani

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W3106209420

FWCI: 0.86

Cites: 16

Cited by: 12

Related to: 10