Cumulatively up to 20% error reduction is achieved relative to the standard <cite>Boulis and Ostendorf (2005)</cite> algorithm for classifying individual conversations on Switchboard, and accuracy for gender detection on the Switchboard corpus (aggregate) and Gulf Arabic exceeds 95%.