Cyrillic Latin Script Transliteration

Cyrillic-Latin script transliteration focuses on converting text between Cyrillic and Latin alphabets, primarily to improve natural language processing (NLP) capabilities for low-resource languages. Current research emphasizes leveraging large language models (LLMs) like BERT and transformer-based architectures, often incorporating techniques like phonetic back-translation and rule-based approaches to enhance accuracy and efficiency. This work is significant because it addresses challenges in cross-lingual transfer learning and improves NLP performance for languages with limited digital resources, impacting applications such as machine translation, sentiment analysis, and offensive language detection.