DeepAI AI Chat
Log In Sign Up

Crowdsourcing Parallel Corpus for English-Oromo Neural Machine Translation using Community Engagement Platform

by   Sisay Chala, et al.

Even though Afaan Oromo is the most widely spoken language in the Cushitic family by more than fifty million people in the Horn and East Africa, it is surprisingly resource-scarce from a technological point of view. The increasing amount of various useful documents written in English language brings to investigate the machine that can translate those documents and make it easily accessible for local language. The paper deals with implementing a translation of English to Afaan Oromo and vice versa using Neural Machine Translation. But the implementation is not very well explored due to the limited amount and diversity of the corpus. However, using a bilingual corpus of just over 40k sentence pairs we have collected, this study showed a promising result. About a quarter of this corpus is collected via Community Engagement Platform (CEP) that was implemented to enrich the parallel corpus through crowdsourcing translations.


page 4

page 5


MIZAN: A Large Persian-English Parallel Corpus

One of the most major and essential tasks in natural language processing...

Synthetic Data for Neural Machine Translation of Spoken-Dialects

In this paper, we introduce a novel approach to generate synthetic data ...

A Parallel Corpus of Theses and Dissertations Abstracts

In Brazil, the governmental body responsible for overseeing and coordina...

Marathi To English Neural Machine Translation With Near Perfect Corpus And Transformers

There have been very few attempts to benchmark performances of state-of-...

Central Kurdish machine translation: First large scale parallel corpus and experiments

While the computational processing of Kurdish has experienced a relative...

Automatic Parallel Corpus Creation for Hindi-English News Translation Task

The parallel corpus for multilingual NLP tasks, deep learning applicatio...

Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish

We develop machine translation and speech synthesis systems to complemen...