- Source
- arXiv.org
- Published
- 5 Mar 2026
- Authors
- Samantha Adorno, Akshata Kishore Moharir, Ratna Kandala
Excerpt from source
Although artificial intelligence (AI) and Human-Computer Interaction (HCI) systems are often presented as universal solutions, their design remains predominantly text-first, underserving primarily oral languages and indigenous communities. This position paper uses Guaran'i, an official and widely spoken language of Paraguay, as a case study to argue that language support in AI remains insufficient unless it aligns with lived oral practices. We propose an alternative to the standard"text-to-speech"pipeline, proposing instead an oral-first multi-agent architecture. By decoupling Guaran'i natural language understanding from dedicated agents for conversation state and community-led…
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