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A Systematic Approach to Derive a Refined Speech Corpus for Sinhala

Speech Recognition is an active research area where advances of technology have continuously driven the development of research work. However, due to the lack of adequate resources, certain languages such as Sinhala, are left to underutilize the technology. With techniques such as crowdsourcing and web scraping, several Sinhala corpora have been created and made publicly available. Despite them being large and generic, the correctness and consistency in their text data remain questionable, especially due to the lack of uniformity in the language used in the different sources of web scraped text. Addressing that requires a thorough understanding of technical and linguistic particulars pertaining to the language, which often leaves the issue unattended. We have followed a systematic approach to derive a refined corpus using a publicly available corpus for Sinhala speech recognition. In particular, we standardized the transcriptions of the corpus by removing noise in the text. Further, we applied corrections based on Sinhala linguistics. A comparative experiment shows a promising effect of the linguistic corrections by having a relative reduction of the Word-Error-Rate by 15.9%.