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Reseach Article

Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM)

by Barinder Singh, Karan Mahajan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 6
Year of Publication: 2015
Authors: Barinder Singh, Karan Mahajan
10.5120/21068-3738

Barinder Singh, Karan Mahajan . Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM). International Journal of Computer Applications. 119, 6 ( June 2015), 1-2. DOI=10.5120/21068-3738

@article{ 10.5120/21068-3738,
author = { Barinder Singh, Karan Mahajan },
title = { Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM) },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 6 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-2 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number6/21068-3738/ },
doi = { 10.5120/21068-3738 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:17.644701+05:30
%A Barinder Singh
%A Karan Mahajan
%T Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM)
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 6
%P 1-2
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech Enhancement refered as to improve quality or intelligibility of speech signal. Speech signal is often degraded by additive background noise like babble noise, train noise, restaurant noise etc. Speech enhancement aims at improving the performance of speech communication systems in noisy environments. This paper proposes a segmental NMF (SNMF) speech enhancement scheme to improve the conventional frame-wise NMF-based method. In this two algorithms are derived to decompose the original nonnegative matrix associated with the magnitude spectrogram, the first algorithm is used in the spectral domain and the second algorithm is used in the temporal domain . In this paper Hidden macro model and SNMF(S) for subjective learning (SNMF-S). Then the SNMF for the objective learning (SNMF-O) will be implemented.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speech Enhancement Non negative Matrix Factorization (NMF) Segmental Nonnegative Matrix Factorization (SNMF)