@inproceedings{0dc7ffd985614237a1338109baf19556,
title = "A review on speech separation using NMF and its extensions",
abstract = "Speech separation aims to estimate the target signals produced by individual speech sources from a mixture signal. In this paper, we especially review on data-driven separation methods, where algorithms will be enhanced to produce better dictionary learning which considers the geometric of input data and efficiently performs separation mixture. We review the existing algorithms using non-negative matrix factorization, sparse coding, mixture local dictionary, group lasso, and graph regularization to produce knowledge bases. We also review the extension of NMF by incorporating two state-of-art techniques i.e. bilevel optimization and deep neural network.",
keywords = "bilevel optimization, graph regularization, group lasso, non-negative matrix factorization, single channel source separation",
author = "Tuan Pham and Lee, {Yuan Shan} and Chen, {Yu An} and Wang, {Jia Ching}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd International Conference on Orange Technologies, ICOT 2015 ; Conference date: 19-12-2015 Through 22-12-2015",
year = "2016",
month = jun,
day = "22",
doi = "10.1109/ICOT.2015.7498486",
language = "???core.languages.en_GB???",
series = "Proceedings of 2015 International Conference on Orange Technologies, ICOT 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "26--29",
booktitle = "Proceedings of 2015 International Conference on Orange Technologies, ICOT 2015",
}