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
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;
Conference_Titel :
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location :
Suwon
Print_ISBN :
978-1-4799-0602-4
DOI :
10.1109/ICISA.2013.6579393