@inproceedings{adorno-etal-2026-oral,
title = "An Oral-first Interactive Agentic System for {G}uaran{\'i} Speakers",
author = "Adorno, Samantha and
Moharir, Akshata Kishore and
Kandala, Ratna",
editor = "Claramunt, German Rigau and
Gamallo, Pablo and
Mu{\~n}oz Guillena, Rafael and
Chiruzzo, Luis and
Mart{\'i}nez C{\'a}mara, Eugenio",
booktitle = "Proceedings of {LANLP}: Bridging {I}bero and {L}atin {A}merican {NLP} Communities",
month = may,
year = "2026",
address = "Palma, Mallorca (Spain)",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.lanlp-1.2/",
doi = "10.63317/5hv8tqw33s2d",
pages = "9--14",
abstract = "Artificial intelligence systems are often presented as universal, yet their interaction paradigms remain predominantly text-first, limiting alignment with primarily oral languages and communicative practices. Using Guaran{\'i}, an official and widely spoken language of Paraguay, as a motivating case, this work examines how language support risks remaining symbolic when spoken interaction is reduced to a speech-to-text interface. We explore an oral-first, multi-agent framing in which turn-taking, repair, shared context, and governance are treated as core components of interaction rather than peripheral features. By separating language understanding from the conversation state and permission mechanisms, the architecture makes conversational structure and control explicit, enabling reasoning over interaction dynamics rather than isolated commands. Framing conversational coordination as a cognitively motivated reasoning problem over shared state connects insights from human dialogue to the design of AI systems that are more interpretable and responsive in oral and low-resource settings."
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<abstract>Artificial intelligence systems are often presented as universal, yet their interaction paradigms remain predominantly text-first, limiting alignment with primarily oral languages and communicative practices. Using Guaraní, an official and widely spoken language of Paraguay, as a motivating case, this work examines how language support risks remaining symbolic when spoken interaction is reduced to a speech-to-text interface. We explore an oral-first, multi-agent framing in which turn-taking, repair, shared context, and governance are treated as core components of interaction rather than peripheral features. By separating language understanding from the conversation state and permission mechanisms, the architecture makes conversational structure and control explicit, enabling reasoning over interaction dynamics rather than isolated commands. Framing conversational coordination as a cognitively motivated reasoning problem over shared state connects insights from human dialogue to the design of AI systems that are more interpretable and responsive in oral and low-resource settings.</abstract>
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%0 Conference Proceedings
%T An Oral-first Interactive Agentic System for Guaraní Speakers
%A Adorno, Samantha
%A Moharir, Akshata Kishore
%A Kandala, Ratna
%Y Claramunt, German Rigau
%Y Gamallo, Pablo
%Y Muñoz Guillena, Rafael
%Y Chiruzzo, Luis
%Y Martínez Cámara, Eugenio
%S Proceedings of LANLP: Bridging Ibero and Latin American NLP Communities
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma, Mallorca (Spain)
%F adorno-etal-2026-oral
%X Artificial intelligence systems are often presented as universal, yet their interaction paradigms remain predominantly text-first, limiting alignment with primarily oral languages and communicative practices. Using Guaraní, an official and widely spoken language of Paraguay, as a motivating case, this work examines how language support risks remaining symbolic when spoken interaction is reduced to a speech-to-text interface. We explore an oral-first, multi-agent framing in which turn-taking, repair, shared context, and governance are treated as core components of interaction rather than peripheral features. By separating language understanding from the conversation state and permission mechanisms, the architecture makes conversational structure and control explicit, enabling reasoning over interaction dynamics rather than isolated commands. Framing conversational coordination as a cognitively motivated reasoning problem over shared state connects insights from human dialogue to the design of AI systems that are more interpretable and responsive in oral and low-resource settings.
%R 10.63317/5hv8tqw33s2d
%U https://aclanthology.org/2026.lanlp-1.2/
%U https://doi.org/10.63317/5hv8tqw33s2d
%P 9-14
Markdown (Informal)
[An Oral-first Interactive Agentic System for Guaraní Speakers](https://aclanthology.org/2026.lanlp-1.2/) (Adorno et al., LANLP 2026)
ACL