In this era of rapid artificial intelligence (AI) expansion, computational approaches are reshaping methods for language documentation and description. We survey the history of computational methods that have been applied to research in languages with limited digital resources and also present cutting-edge methods, such as large language models (LLMs), that have the potential to benefit documentary and descriptive fieldwork. We highlight how these methods affect data collection and annotation, transcription and phonological analysis, morphosyntactic description, and translation. Linguists, natural language processing engineers, and speech communities must consider how the use of computational methods such as data mining and machine learning should influence ethical best practices in linguistic field methods and how communities can continue to guide the documentation and maintenance of their languages in the age of AI. Looking forward, LLMs and making computational methods broadly usable through user interfaces are likely to emerge as prominent themes in documentary and descriptive research.
Moeller et al. (Fri,) studied this question.