NLP Progress in Indigenous Latin American Languages
Atnafu Lambebo Tonja Fazlourrahman Balouchzahi Sabur Butt Olga Kolesnikova Hector Ceballos Alexander Gelbukh Thamar Solorio
The paper focuses on the marginalization of indigenous language communities
in the face of rapid technological advancements. We highlight the cultural
richness of these languages and the risk they face of being overlooked in the
realm of Natural Language Processing (NLP). We aim to bridge the gap between
these communities and researchers, emphasizing the need for inclusive
technological advancements that respect indigenous community perspectives. We
show the NLP progress of indigenous Latin American languages and the survey
that covers the status of indigenous languages in Latin America, their
representation in NLP, and the challenges and innovations required for their
preservation and development. The paper contributes to the current literature
in understanding the need and progress of NLP for indigenous communities of
Latin America, specifically low-resource and indigenous communities in general.