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http://dx.doi.org/10.7776/ASK.2010.29.3.200

Non-Stationary/Mixed Noise Estimation Algorithm Based on Minimum Statistics and Codebook Driven Short-Term Predictor Parameter Estimation  

Lee, Myeong-Seok (세종대학교 정보통신공학과)
Noh, Myung-Hoon (세종대학교 정보통신공학과)
Park, Sung-Joo (전자부품연구원 디지털미디어연구센터)
Lee, Seok-Pil (전자부품연구원 디지털미디어연구센터)
Kim, Moo-Young (세종대학교 정보통신공학과)
Publication Information
The Journal of the Acoustical Society of Korea / v.29, no.3, 2010 , pp. 200-208 More about this Journal
Abstract
In this work, the minimum statistics (MS) algorithm is combined with the codebook driven short-term predictor parameter estimation (CDSTP) to design a speech enhancement algorithm that is robust against various background noise environments. The MS algorithm functions well for the stationary noise but relatively not for the non-stationary noise. The CDSTP works efficiently for the non-stationary noise, but not for the noise that was not considered in the training stage. Thus, we propose to combine CDSTP and MS. Compared with the single use of MS and CDSTP, the proposed method produces better perceptual evaluation of speech quality (PESQ) score, and especially works excellent for the mixed background noise between stationary and non-stationary noises.
Keywords
Minimum statistics; noise estimation; speech enhancement; non-stationary noise; mixed noise;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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