Evolutionary Algorithm for Sinhala to English Translation

TL;DR

This paper presents an evolutionary algorithm-based approach for Sinhala to English machine translation, addressing data scarcity and complex language rules to improve translation accuracy.

Contribution

It introduces a novel use of evolutionary algorithms for translating Sinhala to English, overcoming challenges of limited data and complex linguistic structures.

Findings

Achieved accurate Sinhala to English translation results

Demonstrated effectiveness of EA in understanding Sinhala meaning

Improved grammatical correctness in translated sentences

Abstract

Machine Translation (MT) is an area in natural language processing, which focus on translating from one language to another. Many approaches ranging from statistical methods to deep learning approaches are used in order to achieve MT. However, these methods either require a large number of data or a clear understanding about the language. Sinhala language has less digital text which could be used to train a deep neural network. Furthermore, Sinhala has complex rules therefore, it is harder to create statistical rules in order to apply statistical methods in MT. This research focuses on Sinhala to English translation using an Evolutionary Algorithm (EA). EA is used to identifying the correct meaning of Sinhala text and to translate it to English. The Sinhala text is passed to identify the meaning in order to get the correct meaning of the sentence. With the use of the EA the translation is carried out. The translated text is passed on to grammatically correct the sentence. This has shown to achieve accurate results.