Automatic Text Translation of Multilingual Sentences using Transformer

Abstract

Machine translation from one language to another is a complex problem in machine learning and one in which the machine still cannot achieve satisfactory results. The recent focus for solving this challenge has been on neural machine translation (NMT) techniques, by using architectures such as recurrent neural network (RNN) and long term short memory (LSTM). But the architecture of transformer is able to outperform these NMT techniques. The architecture of the transformer has been successfully utilized to build models that target a single language pair translation or translation among multiple languages. But it currently lacks research in the area of translation of multilingual sentences, where each sentence is in the form of a mixture of languages. In this work we will establish a model based on the transformer architecture that can translate multilingual sentences into a single language, with the help of a multilingual neural machine translation (MNMT) model and custom made datasets.