Text Classification Based on Convolutional Neural Networks and Word Embedding for Low-Resource Languages: Tigrinya

Text Classification Based on Convolutional Neural Networks and Word Embedding for Low-Resource Languages: Tigrinya

This article studies convolutional neural networks for Tigrinya (also referred to as Tigrigna), which is a family of Semitic languages spoken in Eritrea and northern Ethiopia. Tigrinya is a “low-resource” language and is notable in terms of the absence of comprehensive and free data. Furthermore, it...

Full description

Bibliographic Details
Main Authors: Awet Fesseha, Shengwu Xiong, Eshete Derb Emiru, Moussa Diallo, Abdelghani Dahou
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Information
Subjects:
text classification
CNN
low-resource language
machine learning
word embedding
natural language processing
Online Access:https://www.mdpi.com/2078-2489/12/2/52

Internet

https://www.mdpi.com/2078-2489/12/2/52

Similar Items