A perceptually-motivated low-complexity instantaneous linear channel normalization technique applied to speaker verification
A novel method to instantaneously normalize speech features is proposed (LNCC). LNCC does not need any alterations to the statistical modeling. LNCC dramatically compensates for static spectral tilts. LNCC can be more robust to time varying spectral tilts than standard methods. LNCC does not require the computation and storage of additional statistics.
channel robust feature extraction auditorymodels spectral local normalization synchrony detection