DocumentCode
630410
Title
Robust Vocabulary Recognition Model Using Average Estimator Least Mean Square Filter
Author
Sang-Yeob Oh ; Kyung-Yong Chung
Author_Institution
Dept. of Interactive media, Gachon Univ., Seongnam, South Korea
fYear
2013
fDate
24-26 June 2013
Firstpage
1
Lastpage
2
Abstract
Noise estimation and detection algorithm should adopt to a changing environment in a fast manner so they use a LMS filter. However, there are some negative points as well. A LMS filter is very low and it consequently lowers a speech recognition rate. In order to overcome such weak point, I would like to propose a method for the establishment of a robust´ speech recognition model in a noise environment. Since this proposed method allows the cancelation of noise with the AELMS filter in a noise environment, a robust speech recognition model can be established in a noise environment.
Keywords
filtering theory; least mean squares methods; signal denoising; speech recognition; AELMS filter; average estimator least mean square filter; noise cancellation; noise detection algorithm; noise environment; noise estimation algorithm; robust speech recognition model; robust vocabulary recognition model; speech recognition rate; Filtering algorithms; Hidden Markov models; Least squares approximations; Noise; Robustness; Speech; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location
Suwon
Print_ISBN
978-1-4799-0602-4
Type
conf
DOI
10.1109/ICISA.2013.6579393
Filename
6579393
Link To Document