  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.
