COMPARING COMPUTATIONAL LINGUISTICS APPROACHES ACROSS LANGUAGES - Norqobilov, Sanjar (Ижтимоий-гуманитар фанларнинг долзарб муаммолари / Актуальные проблемы социально-гуманитарных наук / Actual Problems of Humanities and Social Sciences., 2024)
This paper provides a comparative study on how core computational linguistics techniques function across typologically diverse languages. With a focus on machine translation (MT), it analyzes the complexities that linguistic variability poses for computational approaches. MT development requires language-specific adaptations rather than a one-size-fits-all model. Through a literature review and cross-linguistic case studies, challenges including word order differences, morphological complexity, lexical ambiguity and inadequate resources are explored across analytic, synthetic, tonal and morphologically-rich languages. Results reveal sites of MT difficulty for languages like Arabic, Chinese, Hindi and Swahili. Discussion centers on how techniques like rule-based, statistical and neural MT are impacted by unique linguistic features, requiring adjustments like morphological analyzers and tailored training data. This indicates the importance of inclusive computational linguistics that moves beyond reliance on English data. The study concludes that flexibility and language-specific customization is needed for algorithms to model the structures of the world’s roughly 7,000 languages effectively.