This paper presents the system employed in the Albayzin 2018 "Search on Speech" Evaluation by the Voice Group of CENATAV. The system used in the Spoken Term Detection (STD) task consists on an Automatic Speech Recognizer (ASR) and a module to detect the terms. The open source Kaldi toolkit is used to build both modules. ASR acoustic models are based on DNN-HMM, S-GMM or GMM-HMM, trained with audio data provided by the organizers and other obtained from ELDA. The lexicon and trigram language model are obtained from the text associated to the audio. The ASR generates the lattices and the word alignments required to detect the terms. Results with development data shown that DNN-HMM model brings up a behavior better or similar to obtained in previous challenges.