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AI and Low Resource Languages

savannamind | AI and Low Resource Languages

Overview

Low-resource languages are those with limited digital data—whether text, speech, or annotated resources—and are often spoken by Indigenous, regional, or marginalized communities.

These languages are significantly underrepresented in AI systems, contributing to broader inequities in technological access and cultural preservation.

Key Challenges:

Data Scarcity: Insufficient datasets for training AI models.
Linguistic Diversity: Unique grammatical structures or phonetics not shared with high-resource languages.
Economic Barriers: Limited commercial incentives for tech companies to invest in these languages.
Ethical Concerns: Risk of cultural erosion if languages are excluded from digital spaces.
Infrastructure Gaps: Lack of standardized scripts, digitization tools, or computational resources.
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