Speech enhancement,
Noise estimation,
Wavelet transform,
Second-generation wavelet transform
A second-generation wavelet based implementation of two adaptive noise
estimation algorithms, which do not require explicit use of voice
activity detector or signal statistics learning process, is introduced.
The fast algorithm utilises a smoothing parameter based on estimation of
the wavelet subbands signal-to-noise ratio of the signal. The second
algorithm is based on tracking the minimum variance of subband noisy
speech signal. A new robust noise-tracking algorithm, which combines a
quantile-based noise estimation technique with a modified version of the
above smoothing approach, is then introduced and its performance is
evaluated and compared to the above two noise estimation methods, using
various speech signals contaminated by different levels and types of
noise.