Voice-Based Agricultural Advisory Services for Low-Literacy Users

Eszter Nagy

Voice-Based Agricultural Advisory Services for Low-Literacy Users

Author(s)	Dr. Eszter Nagy
Country	United States
Abstract	Digital agricultural advisory services can reduce the distance between farmers and timely information on weather, crop management, pests, inputs, livestock, market conditions, and climate-related production risks. However, text-intensive digital extension can reproduce existing inequalities when farmers have limited reading proficiency, use basic mobile phones, communicate primarily in local spoken languages, or share devices within households. Voice-based advisory systems offer an alternative by delivering agricultural information through recorded audio, interactive voice response, toll-free helplines, expert callbacks, and farmer-to-farmer voice forums. This paper develops a conceptual–methodological framework for designing voice-based agricultural advisory services specifically for low-literacy users. The framework integrates five accessibility dimensions: spoken-language relevance, cognitive simplicity, interaction and replay capability, contextual personalization, and trusted human escalation. Prior research demonstrates that voice-based agricultural services can generate substantial farmer demand, alter information-seeking behavior, support technology adoption, and facilitate peer knowledge exchange; however, service effectiveness depends strongly on message timing, language, network reliability, content relevance, trust, and opportunities for interaction. The study therefore rejects the assumption that replacing text with recorded speech is sufficient to achieve inclusive digital extension. A scenario-based analysis compares text-only messaging, generic voice broadcasting, local-language audio, interactive voice response, and personalized voice systems with expert callback capability. Because no original farmer dataset was provided, all quantitative values are explicitly simulated and are not presented as empirical findings. The analysis suggests that voice systems become progressively more accessible when farmers can replay information, navigate simple menus, receive locally relevant advice, and request clarification from trusted agricultural experts. The proposed framework offers a basis for future field experiments, usability studies, gender-sensitive access assessments, and agricultural-extension evaluations.
Keywords	voice-based agricultural advisory, low-literacy farmers, interactive voice response, agricultural extension, digital agriculture, mobile advisory services, rural communication, smallholder farmers
Field	Engineering
Published In	Volume 7, Issue 1, January-February 2026
Published On	2026-01-05

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American Journal of Advanced Multidisciplinary Innovation and Research

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Voice-Based Agricultural Advisory Services for Low-Literacy Users

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