\input zb-basic
\input zb-ioport
\iteman{io-port 06017400}
\itemau{Squartini, Stefano; Principi, Emanuele; Rotili, Rudy; Piazza, Francesco}
\itemti{Environmental robust speech and speaker recognition through multi-channel histogram equalization.}
\itemso{Neurocomputing 78, 111-120 (2012).}
\itemab
Summary: Feature statistics normalization in the cepstral domain is one of the most performing approaches for robust automaticspeech and speaker recognition in noisy acoustic scenarios: feature coefficients are normalized by using suitable linear or nonlinear transformations in order to match the noisy speech statistics to the clean speech one. Histogram equalization (HEQ) belongs to such a category of algorithms and has proved to be effective on purpose and therefore taken here as reference.
\itemrv{~}
\itemcc{}
\itemut{multi-channel audio processing; feature statistics normalization; histogram equalization; speech recognition; speaker recognition}
\itemli{doi:10.1016/j.neucom.2011.05.035}
\end