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This paper proposes an algorithm to perform monaural speech source separation by means of time-frequency masking. The algorithm is based on the estimation of the power spectrum of the original speech signals as a combination of a carrier signal multiplied by an envelope. A Multi-Frequency Harmonic Product Spectrum (MF-HPS) algorithm is used to estimate the fundamental frequency of the signals in the mixture. These frequencies are used to estimate both the carrier and the envelope from the mixture. Binary masks are generated comparing the estimated spectra of the signals. Results show an important improvement in the separation in comparison to the original algorithm that only uses the information from the HPS.
									 Author (s):  Ayllon, David; Gil-Pita, Roberto; Rosa-Zurera, Manuel
								
								 Affiliation: 
								University of Alcala, Alcalá de Henares, Spain
								 (See document for exact affiliation information.)
								
																	 AES Convention: 134
									 Paper Number:8832
									
																 Publication Date: 
								2013-05-06
								 
										
										 Import into BibTeX 
									
									
																			 Session subject: 
										Speech Processing
										
																		 Permalink:  https://aes2.org/publications/elibrary-page/?id=16733							
(352KB)
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Ayllon, David; Gil-Pita, Roberto; Rosa-Zurera, Manuel; 2013; Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum [PDF]; University of Alcala, Alcalá de Henares, Spain; Paper 8832; Available from: https://aes2.org/publications/elibrary-page/?id=16733
Ayllon, David; Gil-Pita, Roberto; Rosa-Zurera, Manuel; Monaural Speech Source Separation by Estimating the Power Spectrum Using Multi-Frequency Harmonic Product Spectrum [PDF]; University of Alcala, Alcalá de Henares, Spain; Paper 8832; 2013 Available: https://aes2.org/publications/elibrary-page/?id=16733
@article{ayllon2013monaural, 
author={ayllon  david and gil-pita  roberto and rosa-zurera  manuel}, 
journal={journal of the audio engineering society}, 
title={monaural speech source separation by estimating the power spectrum using multi-frequency harmonic product spectrum}, 
year={2013}, 
number={8832}, 
month={may},}