A keyword detection system with zero-resources techniques is presented. It consists of a primary alignment method and a later rescoring of its hipotheses. Both stages based on a segmental dynamic time warping method and a segmental model respectively. The resulting system is totally language independent and has no pre-segmentation or written resources requirements, being its only needed input information a set of stored keyword emissions. Recognition rates of 60% with 15% of false positive errors are obtained, and is clearly demonstrated that the rescoring stage improves overall system performance.