We present a resource for computational experiments on Mapudungun, a polysynthetic indigenous language spoken in Chile with upwards of 200 thousand speakers. We provide 142 hours of culturally significant conversations in the domain of medical treatment. The conversations are fully transcribed and translated into Spanish. The transcriptions also include annotations for code-switching and non-standard pronunciations. We also provide baseline results on three core NLP tasks: speech recognition, speech synthesis, and machine translation between Spanish and Mapudungun. We further explore other applications for which the corpus will be suitable, including the study of code-switching, historical orthography change, linguistic structure, and sociological and anthropological studies.
Cite
@article{arxiv.1912.01772,
title = {A Resource for Computational Experiments on Mapudungun},
author = {Mingjun Duan and Carlos Fasola and Sai Krishna Rallabandi and Rodolfo M. Vega and Antonios Anastasopoulos and Lori Levin and Alan W Black},
journal= {arXiv preprint arXiv:1912.01772},
year = {2020}
}