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AI Models for Endangered Language Revitalization
We’re building a small speech corpus (<40 hours) for a severely endangered language. We want to leverage open‑source ASR + LLMs for community learning tools without leaking sacred narratives. Strategies for balancing openness and cultural data sovereignty?
Don’t forget reversible obfuscation of speaker identity (voice conversion toward a neutral timbre) before any cloud processing. Protects elders from having their voice cloned later.
Partition corpora: public pedagogical phrases vs. restricted ceremonial sets. Fine‑tune acoustic model on all audio locally, but only release weights trained on the open subset. Keep a reproducible script so outsiders can re‑train if they gain clearance.
Also adopt a “data governance council” (actual community members) with veto power over model updates. Publish a model card that explicitly lists prohibited downstream uses; it sets a norm even if not legally absolute.
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