With a particular focus on Natural Language Processing (NLP), a subfield of Artificial Intelligence, InkyLab, the dedicated research and development unit of Tunisian news outlet Inkyfada, aims to create new ideas and tools to further innovation within the newsroom.
The unit has developed a range of solutions designed to help Inkyfada reach larger audiences, tailor content to platforms and user preferences, and automate time-consuming tasks for journalists, while also aiming to bridge the gap between languages in the NLP space.
“The first and most important problem that we face is the discrepancy between languages,” said Farouk Ali, Data Scientist & Head of the R&D Unit at InkyLab, during Digital Media Africa conference, adding that there are more than 4,500 English NLP models in existence compared to 161 in Arabic.
As Inkyfada is published in English, French, and Arabic, all solutions developed by InkyLab are made for these three languages.
Some of the projects the team has worked on include a recommendation system, a summary and title generator, as well as speech-to-text and text-to-speech solutions to automatically create an audio version of an article or a transcript of an audio file.
Helping newsrooms achieve gender balance
InkyLab has also been working with text mining, the process of extracting information from structured and unstructured content, which was used extensively in creating the Gender Tracker, a tool developed in partnership with WAN-IF…
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The post Tracking gender balance and analysing online content: Experts share AI use cases appeared first on WAN-IFRA.
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