Text-independent speaker verification by discriminator counting

The authors describe an algorithm for detecting the presence of speech from a particular individual, called the target, while rejecting speech from all other individuals. The algorithm requires samples of training data for the target speaker, as well as for a set of N other speakers, called reference speakers. These data are used to estimate the parameters of a set of speaker-pair discriminators. Each discriminator separates the target from one of the reference speakers, producing a positive or negative value for each input frame. The polarity of discriminators is such that positive output values favor the target. After the discriminator output has been integrated over a suitable time interval, the number of positive values is counted and compared with a detection threshold between 0 and N. In an experiment using clean speech material, 80% of targets were detected with only 2% of non-targets