1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.SD2024★ 1 cited
Study of the Performance of CEEMDAN in Underdetermined Speech Separation
Rawad Melhem, Riad Hamadeh, Assef Jafar
The CEEMDAN algorithm is one of the modern methods used in the analysis of non-stationary signals. This research presents a study of the effectiveness of this method in audio sourc…
cs.SD2024
Developing an Effective Training Dataset to Enhance the Performance of AI-based Speaker Separation Systems
Rawad Melhem, Assef Jafar, Oumayma Al Dakkak
This paper addresses the challenge of speaker separation, which remains an active research topic despite the promising results achieved in recent years. These results, however, oft…
cs.SD2023
Improving Deep Attractor Network by BGRU and GMM for Speech Separation
Rawad Melhem, Assef Jafar, Riad Hamadeh
Deep Attractor Network (DANet) is the state-of-the-art technique in speech separation field, which uses Bidirectional Long Short-Term Memory (BLSTM), but the complexity of the DANe…