Challenges to Prepare the Parallel Corpus for Luganda Language

This research paper explores the challenges associated with preparing a parallel corpus for the Luganda language. Luganda, as a widely spoken Bantu language in Uganda, assumes a crucial role in facilitating communication within the country. However, despite its prominence, there is a scarcity of extensive and high-quality language resources for Luganda currently available. The aim of this study is to address the gap in parallel corpora for Luganda, which is crucial for the development of effective natural language processing (NLP) applications including machine translation and sentiment analysis. The paper discusses various approaches to collecting parallel data, including manual translation, Web scraping, optical character recognition (OCR), and speech transcription. Additionally, the study investigates the existing datasets and resources for Luganda, highlighting their limitations and the need for additional data collection. By examining the challenges and proposing potential solutions, this research contributes to the advancement of Luganda language processing and paves the way for improved cross-lingual communication and language technology applications in the Luganda-speaking community.