Language Documentation

Language documentation, the systematic recording and analysis of languages, is increasingly aided by computational methods aiming to automate time-consuming tasks like phonetic transcription and interlinear glossing. Current research focuses on applying and adapting machine learning models, including transformer architectures and those based on wav2vec 2.0, to handle low-resource languages and improve the accuracy of automated processes such as code summarization and GUI-based software documentation. These advancements have the potential to significantly accelerate the documentation of endangered languages and improve the efficiency of software development, contributing to both linguistic preservation and technological progress.