DocumentCode
3095702
Title
Notice of Retraction
An real-time voice activity robust detection based on subband spectrum
Author
Wang Jingfang
Author_Institution
Dept. of Electr. Eng., Hunan Int. Econ. Univ., Changsha, China
Volume
3
fYear
2011
fDate
8-9 Sept. 2011
Firstpage
200
Lastpage
203
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a complex environment to adapt to the efficient real-time endpoint detection algorithm, each frame is given in the acoustic signal in the noise power spectrum filtering the projection method. First spectrum of each frame iteration voice filtering, then it is divided into several sub-bands and calculate the entropy of each subband spectrum, and then have a number of sub-band spectral entropy of the frame after a median filter to obtain a set of Spectral entropy of each frame, according to the value of spectral entropy to classify the input voice. Experimental results show that the algorithm can distinguish speech and noise, can significantly improve the performance of speech recognition systems, in different environmental conditions, noise robust. The algorithm to calculate the cost of a small, simple and easy to implement for real-time voice recognition system.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a complex environment to adapt to the efficient real-time endpoint detection algorithm, each frame is given in the acoustic signal in the noise power spectrum filtering the projection method. First spectrum of each frame iteration voice filtering, then it is divided into several sub-bands and calculate the entropy of each subband spectrum, and then have a number of sub-band spectral entropy of the frame after a median filter to obtain a set of Spectral entropy of each frame, according to the value of spectral entropy to classify the input voice. Experimental results show that the algorithm can distinguish speech and noise, can significantly improve the performance of speech recognition systems, in different environmental conditions, noise robust. The algorithm to calculate the cost of a small, simple and easy to implement for real-time voice recognition system.
Keywords
acoustic signal processing; entropy; median filters; speech recognition; acoustic signal; median filter; noise power spectrum filtering; projection method; real-time endpoint detection algorithm; real-time voice activity robust detection; real-time voice recognition system; speech recognition systems; subband spectral entropy; subband spectrum; voice filtering; Entropy; Real time systems; Signal to noise ratio; Speech; Speech recognition; Wiener filter; Endpoint detection; adaptive processing; iterative Wiener filter; robustness; subband spectral entropy;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location
Wuhan
Print_ISBN
978-1-4244-9691-4
Type
conf
DOI
10.1109/PEAM.2011.6135045
Filename
6135045
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