Longa: An automated speech recognition tool for Bantu languages
Farm Radio International (FRI) and the CGIAR Research Initiative on Digital Innovation have col laborated on the development of an end-to-end, automatic speech recognition pipeline for the tran scription, translation, and analysis of Swahili and Luganda. This task is particularly challenging due to...
| Autores principales: | , , , |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
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International Food Policy Research Institute
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/137177 |
| _version_ | 1855534447998271488 |
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| author | Mganga, Nelson Jones-Garcia, Eliot Monsalue, Andrea Gardeazabal Koo, Jawoo |
| author_browse | Jones-Garcia, Eliot Koo, Jawoo Mganga, Nelson Monsalue, Andrea Gardeazabal |
| author_facet | Mganga, Nelson Jones-Garcia, Eliot Monsalue, Andrea Gardeazabal Koo, Jawoo |
| author_sort | Mganga, Nelson |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Farm Radio International (FRI) and the CGIAR Research Initiative on Digital Innovation have col laborated on the development of an end-to-end, automatic speech recognition pipeline for the tran scription, translation, and analysis of Swahili and Luganda. This task is particularly challenging due to the number of languages used by FRI's clients and the limited training data available for speech recognition in African languages. The tool is named 'Longa', or 'Let's chat' in Swahili. Longa will be used to answer the surplus of phone calls currently being received from smallholder farmers asking questions about radio programs which FRI does not presently have the capacity to address. When fully implemented, Longa should allow FRI to design their broadcasts more intricately in line with the needs of farmers and better deliver insights to those most in need, such as female and youth farmers. Key results from the collaboration include a series of design principles iteratively and col laboratively developed to reflect the common values and goals of FRI and the CGIAR, a proof of concept for Longa, building on open-source models and open access corpora, to be shared with the developer community upon completion of the final tool, a 10% improvement upon the state-of-the art automatic speech recognition in Luganda radio-speech performance and accuracy, some im provement in performance with audio enhancement processes using real-world data, and proof that fine-tuning is an effective approach to expanding Longa to new languages. The next steps of the collaboration will focus on the analysis and interpretation of an aggregation of farmer phone calls and integration with the existing FRI workflow and software. |
| format | Informe técnico |
| id | CGSpace137177 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1371772025-11-06T07:10:25Z Longa: An automated speech recognition tool for Bantu languages Mganga, Nelson Jones-Garcia, Eliot Monsalue, Andrea Gardeazabal Koo, Jawoo artificial intelligence innovation adoption languages farmers Farm Radio International (FRI) and the CGIAR Research Initiative on Digital Innovation have col laborated on the development of an end-to-end, automatic speech recognition pipeline for the tran scription, translation, and analysis of Swahili and Luganda. This task is particularly challenging due to the number of languages used by FRI's clients and the limited training data available for speech recognition in African languages. The tool is named 'Longa', or 'Let's chat' in Swahili. Longa will be used to answer the surplus of phone calls currently being received from smallholder farmers asking questions about radio programs which FRI does not presently have the capacity to address. When fully implemented, Longa should allow FRI to design their broadcasts more intricately in line with the needs of farmers and better deliver insights to those most in need, such as female and youth farmers. Key results from the collaboration include a series of design principles iteratively and col laboratively developed to reflect the common values and goals of FRI and the CGIAR, a proof of concept for Longa, building on open-source models and open access corpora, to be shared with the developer community upon completion of the final tool, a 10% improvement upon the state-of-the art automatic speech recognition in Luganda radio-speech performance and accuracy, some im provement in performance with audio enhancement processes using real-world data, and proof that fine-tuning is an effective approach to expanding Longa to new languages. The next steps of the collaboration will focus on the analysis and interpretation of an aggregation of farmer phone calls and integration with the existing FRI workflow and software. 2023-12-31 2024-01-04T20:42:09Z 2024-01-04T20:42:09Z Report https://hdl.handle.net/10568/137177 en Open Access application/pdf International Food Policy Research Institute Mganga, Nelson; Jones-Garcia, Eliot; Monsalue, Andrea Gardeazabal; and Koo, Jawoo. 2023. Longa: An automated speech recognition tool for Bantu languages. Digital Innovation Technical Report December 2023. Washington, DC: International Food Policy Research Institute (IFPRI). https://hdl.handle.net/10568/137177 |
| spellingShingle | artificial intelligence innovation adoption languages farmers Mganga, Nelson Jones-Garcia, Eliot Monsalue, Andrea Gardeazabal Koo, Jawoo Longa: An automated speech recognition tool for Bantu languages |
| title | Longa: An automated speech recognition tool for Bantu languages |
| title_full | Longa: An automated speech recognition tool for Bantu languages |
| title_fullStr | Longa: An automated speech recognition tool for Bantu languages |
| title_full_unstemmed | Longa: An automated speech recognition tool for Bantu languages |
| title_short | Longa: An automated speech recognition tool for Bantu languages |
| title_sort | longa an automated speech recognition tool for bantu languages |
| topic | artificial intelligence innovation adoption languages farmers |
| url | https://hdl.handle.net/10568/137177 |
| work_keys_str_mv | AT mganganelson longaanautomatedspeechrecognitiontoolforbantulanguages AT jonesgarciaeliot longaanautomatedspeechrecognitiontoolforbantulanguages AT monsalueandreagardeazabal longaanautomatedspeechrecognitiontoolforbantulanguages AT koojawoo longaanautomatedspeechrecognitiontoolforbantulanguages |