DocumentCode
495300
Title
An Improved Endpoint Detection Algorithm with Low Signal-to-Noise Ratio
Author
Wang Yue ; Zhihong, Qian ; Xiuli, Wang
Author_Institution
Coll. of Commun. Eng., Jilin Univ., Changchun, China
Volume
6
fYear
2009
fDate
March 31 2009-April 2 2009
Firstpage
121
Lastpage
125
Abstract
An endpoint detection algorithm that combines expanded spectral subtraction with the SAP (speech absence probability) soft decision is proposed based on traditional methods. The algorithm employs a method of expanded spectral subtraction based on the noise compensation structure, which can estimate the noise during speech presence. A method of endpoint detection based on the SAP soft decision is given, which improves robustness and precision of endpoint detection. The experiments show that better performance can be obtained even if SNR is equal to -10 dB whereas such performance cannot be achieved by traditional energy-based methods with the same SNR.
Keywords
signal detection; speech recognition; endpoint detection algorithm; expanded spectral subtraction; low signal-to-noise ratio; speech absence probability soft decision; speech recognition; traditional energy-based methods; Automatic speech recognition; Background noise; Degradation; Detection algorithms; Detectors; Noise robustness; Signal to noise ratio; Speech enhancement; Speech recognition; Working environment noise; Endpoint detection; Expanded spectral subtraction; Speech absence probability;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location
Los Angeles, CA
Print_ISBN
978-0-7695-3507-4
Type
conf
DOI
10.1109/CSIE.2009.443
Filename
5170673
Link To Document