DocumentCode
675608
Title
One microphone speech separaction with deep belief network
Author
Jie Lin ; Bo Fu ; Jianzhang Chen ; Jie Zheng
Author_Institution
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear
2013
fDate
17-19 Dec. 2013
Firstpage
21
Lastpage
24
Abstract
In this paper, we proposed a novel method for speech separation under one-microphone input. The method employs the deep belief networks to build the speech magnitude estimator, which provides a soft mask for extracting the desired speech from the input signal mixed with interference signals. The new approach has been evaluated on mixture speech data and the results demonstrated its efficiency.
Keywords
microphones; speech processing; deep belief network; desired speech extraction; input signal; interference signals; mixture speech data; one microphone speech separation; one-microphone input; soft mask; speech magnitude estimator; Feature extraction; Hidden Markov models; Probability distribution; Speech; Stochastic processes; Training; Vectors; Speech separation; deep belief network; magnitude estimator;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2013 10th International Computer Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-2445-5
Type
conf
DOI
10.1109/ICCWAMTIP.2013.6716592
Filename
6716592
Link To Document