Keyword Spotter Model for Crop Pest and Disease Monitoring from Community Radio Data

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dc.contributor.authorAkera, Benjamin
dc.contributor.authorNakatumba-Nabende, Joyce
dc.contributor.authorMukiibi, Jonathan
dc.contributor.authorHussein, Ali
dc.contributor.authorBaleeta, Nathan
dc.contributor.authorSsendiwala, Daniel
dc.contributor.authorNalwooga, Samiiha
dc.date.accessioned2022-12-29T13:12:02Z
dc.date.available2022-12-29T13:12:02Z
dc.date.issued2019
dc.description.abstractIn societies with well developed internet infrastructure, social media is the leading medium of communication for various social issues especially for breaking news situations. In rural Uganda however, public community radio is still a dominant means for news dissemination. Community radio gives audience to the general public especially to individuals living in rural areas, and thus plays an important role in giving a voice to those living in the broadcast area. It is an avenue for participatory communication and a tool relevant in both economic and social development.This is supported by the rise to ubiquity of mobile phones providing access to phone-in or text-in talk shows. In this paper, we describe an approach to analysing the readily available community radio data with machine learning-based speech keyword spotting techniques. We identify the keywords of interest related to agriculture and build models to automatically identify these keywords from audio streams. Our contribution through these techniques is a cost-efficient and effective way to monitor food security concerns particularly in rural areas. Through keyword spotting and radio talk show analysis, issues such as crop diseases, pests, drought and famine can be captured and fed into an early warning system for stakeholders and policy makers.en_US
dc.identifier.citationAkera, B., Nakatumba-Nabende, J., Mukiibi, J., Hussein, A., Baleeta, N., Ssendiwala, D., & Nalwooga, S. (2019). Keyword Spotter Model for Crop Pest and Disease Monitoring from Community Radio Data. arXiv preprint arXiv:1910.02292.en_US
dc.identifier.urihttps://arxiv.org/abs/1910.02292
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/6743
dc.language.isoenen_US
dc.publisherarXiv preprint arXiven_US
dc.subjectKeyword Spotter Modelen_US
dc.subjectCrop Pest and Disease Monitoringen_US
dc.subjectCommunity Radio Dataen_US
dc.titleKeyword Spotter Model for Crop Pest and Disease Monitoring from Community Radio Dataen_US
dc.typeArticleen_US
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