Karim is a music enthusiast who got his master’s from Nile University in Egypt in 2016. His master’s thesis focused on audio source separation and the problem of primary and ambient sounds. He wrote his thesis while interning at Sony’s Stuttgart Technology Center. Afterwards, he joined the PhD program at NUS and is currently working on the problem of lyrics intelligibility and its applications in education. His research interests include music analysis, machine learning, and singing voice.
Karim M. Ibrahim, David Grunberg, Kat Agres, Chitralekha Gupta, and Ye Wang (2017). Intelligibility of Sung Lyrics: A Pilot Study. Proceedings of the 18th International Society for Music Information Retrieval Conference, ISMIR 2017, Suzhou, China.
Ibrahim, K. M., et al. “Primary-Ambient Extraction in Audio Signals Using Adaptive Weighting and Principal Component Analysis” Proceedings of the 13th Sound and Music Computing Conference (SMC). 2016.