Speaker: 'Text-Based and Speech-Based Automatic Dialect Identification for the Arabic Language'
This event is part of the Spring 2022 Middle Eastern and North African Studies Colloquium Series.
Dialect Identification is a special case of Language Identification that presents specific challenges and problems related to the linguistic similarity between dialects. Even though LID can be considered a well-understood problem, closely related dialects and language varieties still pose significant challenges for their automatic recognition. This talk presents two published papers on Arabic Dialect identification.
Our speaker, Elsayed Issa, is currently a doctoral candidate specializing in Arabic linguistics at the School of Middle Eastern and North African Studies at the University of Arizona. He obtained his M.A. degree in Machine Translation from Alexandria University in Egypt. His thesis involved designing software for translating simple English sentences into their Arabic equivalents.His research interests include phonology, morphology, natural language processing, machine learning, blended learning and education technology.
This event will be hybrid, both via Zoom and in person in Marshall 490. To learn more and register, please visit the link below.