NWS seeks machine learning to translate hurricane warnings

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To better serve Spanish speaking communities across the country, the National Weather Service is looking for machine learning powered translation.

The National Weather Service (NWS), is requesting information on machine-learning technology that can translate weather forecasts and warnings into Spanish and other languages.

NWS often issues information and alerts to its partners and the general public via text messages. Currently, the NWS Weather Forecast Office in San Juan manually translates information from the National Hurricane Center’s Atlantic basin into Spanish – a practice which is unsustainable, according to the draft requirements.

Initially, NWS wants to use ML tools to create a "first guess" Spanish translation, so the San Juan forecasters can more quickly translate the products manually.  

Eventually, NWS aims to use a cloud-based solution to generate on-the-fly translations of free text, documents, webpage and social media content. These would include Microsoft Powerpoint and Word files, PDFs and Google docs and slides. The tool must use the same machine learning base model across messaging platforms to make sure that all the content is translated using the same baseline source material.

The software should use artificial intelligence to fine-tune and improve the translations of weather jargon, such that Spanish speakers of different dialects will understand the gist of the messages. Ideally, the algorithm will also leverage social science and linguistic research to communicate with the words that are most effective within certain populations.

Read the full RFI here.

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