Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension
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 pr...
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
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International Maize and Wheat Improvement Center
2022
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| Acceso en línea: | https://hdl.handle.net/10568/127005 |
| _version_ | 1855542168683282432 |
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| author | Jones-Garcia, Eliot |
| author_browse | Jones-Garcia, Eliot |
| author_facet | Jones-Garcia, Eliot |
| author_sort | Jones-Garcia, Eliot |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Informe técnico |
| id | CGSpace127005 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | International Maize and Wheat Improvement Center |
| publisherStr | International Maize and Wheat Improvement Center |
| record_format | dspace |
| spelling | CGSpace1270052025-11-06T13:15:26Z Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension Jones-Garcia, Eliot artificial intelligence data analysis data agricultural extension automation technology 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. 2022-11-22 2023-01-12T21:27:38Z 2023-01-12T21:27:38Z Report https://hdl.handle.net/10568/127005 en Open Access application/pdf International Maize and Wheat Improvement Center 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). |
| spellingShingle | artificial intelligence data analysis data agricultural extension automation technology Jones-Garcia, Eliot Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title | Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title_full | Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title_fullStr | Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title_full_unstemmed | Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title_short | Speech recognition, machine translation, and corpus analysis for identifying farmer demands and targeting digital extension |
| title_sort | speech recognition machine translation and corpus analysis for identifying farmer demands and targeting digital extension |
| topic | artificial intelligence data analysis data agricultural extension automation technology |
| url | https://hdl.handle.net/10568/127005 |
| work_keys_str_mv | AT jonesgarciaeliot speechrecognitionmachinetranslationandcorpusanalysisforidentifyingfarmerdemandsandtargetingdigitalextension |