Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

被引:0
作者
Peter Händel
机构
[1] Royal Institute of Technology,Signal Processing Lab, School of Electrical Engineering
来源
EURASIP Journal on Advances in Signal Processing | / 2007卷
关键词
Spectral Density; Power Spectral Density; Performance Assessment; Power Spectral; Independent Research;
D O I
暂无
中图分类号
学科分类号
摘要
A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.
引用
收藏
相关论文
共 50 条
[41]   General Form of the Power Spectral Density of Multicarrier Signals [J].
Lopez-Valcarce, Roberto .
IEEE COMMUNICATIONS LETTERS, 2022, 26 (08) :1755-1759
[42]   Distributed Estimation of Smooth Graph Power Spectral Density [J].
Gama, Fernando ;
Ribeiro, Alejandro .
2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, :643-647
[43]   Low-complexity Power Spectral Density Estimation [J].
Balasaraswathy, N. ;
Rajavel, R. .
ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY ALGORITHMS IN ENGINEERING SYSTEMS, VOL 2, 2015, 325 :273-282
[44]   More systematic errors in the measurement of power spectral density [J].
Mack, Chris A. .
JOURNAL OF MICRO-NANOLITHOGRAPHY MEMS AND MOEMS, 2015, 14 (03)
[45]   The power spectral density of the conditional markov pulse process [J].
Ushakov, Yu. V. ;
Dubkov, A. A. .
MOSCOW UNIVERSITY PHYSICS BULLETIN, 2010, 65 (05) :372-377
[46]   More systematic errors in the measurement of power spectral density [J].
Mack, Chris A. .
METROLOGY, INSPECTION, AND PROCESS CONTROL FOR MICROLITHOGRAPHY XXIX, 2015, 9424
[47]   Blind Source Separation Based on Power Spectral Density [J].
Wang, JingHui ;
Zhao, YuanChao .
ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PT II, 2011, 7003 :602-609
[48]   Riemannian Distances for Signal Classification by Power Spectral Density [J].
Li, Yili ;
Wong, Kon Max .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2013, 7 (04) :655-669
[49]   Estimation of Power Spectral Density using Wavelet Thresholding [J].
Sysel, Petr ;
Misurec, Jiri .
PROCEEDINGS OF THE 7TH WSEAS INTERNATIONAL CONFERENCE ON CIRCUITS, SYSTEMS, ELECTRONICS, CONTROL AND SIGNAL PROCESSING (CSECS'08), 2008, :207-+
[50]   Power Spectral Density Evaluation of Laser Milled Surfaces [J].
Lorbeer, Raoul-Amadeus ;
Pastow, Jan ;
Sawannia, Michael ;
Klinkenberg, Peter ;
Foerster, Daniel Johannes ;
Eckel, Hans-Albert .
MATERIALS, 2018, 11 (01)