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Languages are classified as low-resource when they lack the quantity of datanecessary for training statistical and machine learning tools and models.Causes of resource scarcity vary but can include poor access to technology fordeveloping these resources, a relatively small population of speakers, or alack of urgency for collecting such resources in bilingual populations wherethe second language is high-resource. As a result, the languages described aslow-resource in the literature are as different as Finnish on the one hand,with millions of speakers using it in every imaginable domain, and Seneca, withonly a small-handful of fluent speakers using the language primarily in arestricted domain. While issues stemming from the lack of resources necessaryto train models unite this disparate group of languages, many other issues cutacross the divide between widely-spoken low resource languages and endangeredlanguages. In this position paper, we discuss the unique technological,cultural, practical, and ethical challenges that researchers and indigenousspeech community members face when working together to develop languagetechnology to support endangered language documentation and revitalization. Wereport the perspectives of language teachers, Master Speakers and elders fromindigenous communities, as well as the point of view of academics. We describean ongoing fruitful collaboration and make recommendations for futurepartnerships between academic researchers and language community stakeholders.

Not always about you: Prioritizing community needs when developing endangered language technology