Robust voice activity detection at noisy environment using average estimate least mean square filter
- Authors
- Oh, S.-Y.; Ahn, C.-S.
- Issue Date
- 2013
- Keywords
- AELMS Filter; Clustering Model
- Citation
- 2013 International Conference on Information Science and Applications, ICISA 2013
- Journal Title
- 2013 International Conference on Information Science and Applications, ICISA 2013
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14947
- DOI
- 10.1109/ICISA.2013.6579394
- ISSN
- 0000-0000
- Abstract
- In this paper, noise gets reduced with an average estimate LMS filter in a car noise environment so robust voice activities are being detected in a car noise environment. For the noise reduction, an average estimate LMS filter, which is a method for maintaining a source feature of speech and decreasing damages on speech information, is used in a speech signal detection process to reduce noise from a polluted speech signal. An average estimator was calculated and a step size of a LMS filter was controlled with a frame measure to improve an adaptation speed. Moreover, the starting point of result speech, comparing to the previous method of using frame energy was found to be improved by 1.7% and 3.7% of an error rate and an end point error rate, respectively. © 2013 IEEE.
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Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
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