Afonja, TejumadeMbataku, ClintonOkubadejo, OlumideMalomo, AdemolaNwadike, Munachiso S.Orife, Iroro2021-05-172021-05-172021-05http://hdl.handle.net/10625/60116The paper demonstrates the use case for SautiLearn, a tool that can help students to learn in localized language accents. The work focuses on converting audio speech from one accent to another using a sequence-to-sequence neural network model that uses speaker-independent linguistic features such as the phonetic posterior gram as input. SautiDB is a dataset collection platform that collects speech recordings of various Nigerian accents through the power of crowdsourcing. Together with SautiDB, the SautiDB-919 dataset contains 919 speech samples collected via crowdsourcing through the SautiDB web application platform. The dataset covers a wide range of ethnicities and Nigerian accent variants.application/pdfenAI4DARTIFICIAL INTELLIGENCEAFRICAN LANGUAGESDATABASESLANGUAGESLANGUAGE BARRIERSTRANSLATIONLOCALIZATIONLINGUISTICSMACHINE AIDED TRANSLATIONCOMPUTER APPLICATIONSSOUTH OF SAHARANIGERIAConference Paper