TY - GEN
T1 - Wavelet-Based Noise Estimation Techniques for speech enhancement
AU - Jafer, E.
AU - Mahdi, A. E.
N1 - Publisher Copyright:
© Firenze University Press 2003.
PY - 2003
Y1 - 2003
N2 - In this paper, we describe the implementation of three noise estimation algorithms using two different wavelet decomposition methods: Second-generation and Perceptual wavelet packet transform. The three-presented algorithms are: (a) smoothing based adaptive noise estimation, (b) quantile based noise estimation and (c) minimum variance tracking-based noise estimation These algorithms, which do not need a speech activity detector nor signal statistics learning histograms, are based on estimating the noise power from the noisy speech itself. The performance of presented algorithms has been evaluated and compared for different noise types and levels. A new robust noise estimation technique utilizing a combination of the quantile-based and smoothing based algorithms has been proposed. Reported results demonstrate how these algorithms are capable to track different noise types adequately but with varying degree of accuracy.
AB - In this paper, we describe the implementation of three noise estimation algorithms using two different wavelet decomposition methods: Second-generation and Perceptual wavelet packet transform. The three-presented algorithms are: (a) smoothing based adaptive noise estimation, (b) quantile based noise estimation and (c) minimum variance tracking-based noise estimation These algorithms, which do not need a speech activity detector nor signal statistics learning histograms, are based on estimating the noise power from the noisy speech itself. The performance of presented algorithms has been evaluated and compared for different noise types and levels. A new robust noise estimation technique utilizing a combination of the quantile-based and smoothing based algorithms has been proposed. Reported results demonstrate how these algorithms are capable to track different noise types adequately but with varying degree of accuracy.
UR - http://www.scopus.com/inward/record.url?scp=85133382686&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85133382686
T3 - Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003
SP - 61
EP - 64
BT - Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003
PB - Firenze University Press
T2 - 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003
Y2 - 10 December 2003 through 12 December 2003
ER -