Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension
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Jones-Garcia, Eliot. 2022. Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension. CGIAR Technical Report International Maize and Wheat Improvement Center (CIMMYT).
Permanent link to cite or share this item: https://hdl.handle.net/10568/127005
The increasing capabilities of Artificial Intelligence-augmented data analytics present significant opportunities for agricultural extension organizations operating in the Global South. In this project, we supported Farm Radio International (FRI) in investigating the possibility of automating the process of translating and analyzing farmers' voice message data. This report reviews several approaches to overcoming technical constraints and then presents a cutting-edge approach that utilizes innovations in unsupervised learning to deliver highly accurate speech recognition and machine translation in a diverse set of languages.