This paper presents and discusses keyword spotting methods for searching in speech. In contrast with searching in text, the searching in speech or generally in multimedia data still represents a challenge. The aim of the paper is to present a keyword spotting (KWS) method based on a large vocabulary continuous speech recognition (LVCSR) system, based on phonetics decoder, and keyword spotting using a filler model. All the methods are evaluated and compared from various points of view - speed, quality, requirements on training data and so on. All experiments are done using a telephone-quality speech corpus. Furthermore, this paper presents a new block decision in filler model-based keyword spotting which brings the speedup of decision together with better detection.