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Code-mixed Romanized Sinhala Text to Speech System - 'SINGLISHVOICE'

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dc.contributor.author Uluwatta, Chamika
dc.date.accessioned 2026-05-04T07:23:51Z
dc.date.available 2026-05-04T07:23:51Z
dc.date.issued 2025
dc.identifier.citation Uluwatta, Chamika (2025) Code-mixed Romanized Sinhala Text to Speech System - 'SINGLISHVOICE'. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20210874
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/3249
dc.description.abstract The use of Code-mixed Romanized Sinhala (known also as 'Singlish') in digital communication has left a gap in the current text to speech (TTS) systems that are limited to native Sinhala script. Current TTS models are not able to handle informal spelling variations, shorthand notations, code- mixed Romanized words. In this work, Author proposed a fine-tuned NLLB (No Language Left Behind) model for back transliteration of Romanized Sinhala to native Sinhala as well as a VITS (Vocoder Free TTS) model for high quality speech synthesis. It is implemented with a modular and scalable architecture with a user-friendly Graphical User Interface (GUI) for easy text input and speech generation. The evaluation metrics, such as Word Error Rate (WER), Character Error Rate (CER) and BLEU scores, show that the NLLB model reaches an 21% WER, 58% BLEU, 6% CER, and the VITS TTS model shows MOS 3.8 for male speaker and MOS 2.6 female speaker. Nevertheless, code mixed sentences still pose a challenge in handling them accurately and voice naturalness remains a challenge for female speakers. This study presents the findings that will positively contribute to the progress of Sinhala speech technology and bridge the gap of accessibility for users who utilized TTS technology. en_US
dc.language.iso en en_US
dc.subject Natural Language Processing en_US
dc.subject Machine Translation en_US
dc.title Code-mixed Romanized Sinhala Text to Speech System - 'SINGLISHVOICE' en_US
dc.type Thesis en_US


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