Swa Bhasha: Message-Based Singlish to Sinhala Transliteration

Authors

Maneesha U. Athukorala and Deshan K. Sumanathilaka

Keywords

rule-based machine transliteration, singlish words, sinhala transliteration, swa bhasha

Issue Date

18th February 2022

Abstract

Machine Transliteration provides the ability to transliterate a basic language into different languages in a computational way. Transliteration is an important technical process that has caught the attention most recently. The Sinhala transliteration has many constraints because of the insufficiency of resources in the Sinhala language. Due to these limitations, Sinhala Transliteration is highly complex and time-consuming. Therefore, the majority of the Sri Lankans uses non-formal texting language named ‘Singlish’ to make that process simple. This study has focused on the transliteration of the Singlish language at the word level by reducing the complication in the transliteration. A new approach of coding system has invented with the rule-based approach that can map the matching Sinhala words even without the vowels. Various typing patterns were collected by different communities for this. The collected data have analyzed with every Sinhala character and unique Singlish patterns related to them were generated. The system has introduced a newly initiated numeric coding system to use with the Singlish letters by matching with the recognized typing patterns. For the mapping process, fuzzy logic-based implementation has used. A codified dictionary has also implemented including unique numeric values. In this system, Each Romanized English letter was assigned with a unique numeric code that can construct a unique pattern for each word. The system can identify the most relevant Sinhala word that matches with the pattern of the Singlish word or it gives the most related word suggestions. For example, the word “kiyanna,kianna, kynna, kynn, kiynna” have mapped with the accurate Sinhala word “කියන්න ”. The system has presented 84% of accuracy in word-level and 92% of accuracy in suggestion-level prediction. These results revealed that the“Swa Bhasha” transliteration system has the ability to enhancethe Sinhala users’ experience while conducting the texting in Singlish to Sinhala.