Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension

dc.creatorJones-Garcia, E.
dc.date2023-01-11T19:33:44Z
dc.date2023-01-11T19:33:44Z
dc.date2022
dc.date.accessioned2023-07-17T20:10:01Z
dc.date.available2023-07-17T20:10:01Z
dc.identifierhttps://hdl.handle.net/10883/22379
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7514126
dc.descriptionThe 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.
dc.languageEnglish
dc.publisherCIMMYT
dc.publisherFarm Radio International
dc.relationPoverty reduction, livelihoods & jobs
dc.relationDigital Innovation
dc.relationSystems Transformation
dc.relationCGIAR Trust Fund
dc.relationhttps://hdl.handle.net/10568/127005
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
dc.rightsOpen Access
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectARTIFICIAL INTELLIGENCE
dc.subjectDATA ANALYSIS
dc.subjectAGRICULTURAL EXTENSION
dc.subjectSMALLHOLDERS
dc.subjectSustainable Agrifood Systems
dc.titleSpeech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension
dc.typeReport
dc.typePublished Version
dc.coverageMexico


Este ítem pertenece a la siguiente institución