We present a system consisting of a spiking cochlea chip and real-time event-based processing software that is able to discriminate between two sets of sounds based on their periodicity content. The periodicity measurements are computed from the spike timing information of asynchronous output spikes from the binaural spiking-cochlea chip. The chip consists of a matched pair of silicon cochlea with an address event interface for the output. Each section of the cochlea is modeled by a second-order low-pass filter followed by a simplified inner hair cell circuit and a spiking neuron circuit. We show discrimination results using the periodicity measure for 2 classes of sound and preliminary localization results based on a discriminated sound.