Editorial for the Special Issue on Computational Linguistics Processing in Low-Resource Indigenous Languages
Gautam Srivastava, Jerry Chun‐Wei Lin, Prof. Yu-Dong Zhang · ACM Transactions on Asian and Low-Resource Language Information Processing · 2023
Many of the indigenous languages today are struggling to survive, and they are in danger of disappearing.Closely followed by Africa, Asia has the most indigenous languages.Though indigenous languages have many sources in existence from where we can obtain acceptable knowledge, mythology, history, and perception of their communities, their diversity is decreasing at an alarming rate due to social pressure, external forces, and demographic changes.The systematic disappearance of indigenous languages threatens the lives of millions of families, children, and indigenous communities as well as the survival of their languages worldwide.Most indigenous languages have no written form; which makes them difficult to process and analyze using computational models.However, these languages need to be preserved as they are rich in oral traditions, and they remain remarkably consistent and reliable over time.Presently, many researchers and scientists are actively finding more evidence on indigenous languages to create language processing models using a variety of techniques.Exploring more in terms of grammar, words, and unique rules of sound help us understand the language intuitively and create more efficient linguistic models.However, this process generally tends to be more complex as these languages have very few resources and are often spoken in remote areas by fewer people.Computational linguistics applies computer science techniques for the analysis and synthesis of written and spoken languages.The practical goal of using computational linguistics for indigenous languages is comprehensive.It helps formulate semantic and grammatical frameworks for distinguishing languages through the computationally manageable implementation of semantic and syntactic analysis.Hence, the discovery of more advanced computational linguistics processing algorithms and learning principles that can effectively use the structural and distributional properties of indigenous languages is crucial.It helps develop cognitively and neuroscientifically reasonable computational models that work in the same way that indigenous language processing and learning might occur in the brain.This special issue was dedicated to explain how computational linguistics and natural language processing algorithms make inferences and gain insights into existing data of low-resource indigenous languages.The content mainly focuses on innovative research that formalizes human communication and spoken indigenous languages into the computational system.We welcomed researchers and practitioners from industry and academia to present their contributions against this background.This special issue saw a total of 21 submissions, from which five papers were published.It was intentional to adhere to a strict acceptance rate and ensure that only the best papers in the scope of