The objective of this paper is to study the effect of speaking mode on spoken term detection (STD) system. The experiments are conducted with respect to query words recorded in isolated manner and words cut out from continuous speech. Durations of phonemes in query words greatly vary between these two modes. Hence pattern matching stage plays a crucial role which takes care of temporal variations. Matching is done using Subsequence dynamic time warping (DTW) on posterior features of query and reference utterances, obtained by training Multilayer perceptron (MLP). The difference in performance of the STD system for different phoneme groupings (45, 25, 15 and 6 classes) is also analyzed. Our STD system is tested on Telugu broadcast news. Major difference in STD system performance is observed for recorded and cut-out types of query words. It is observed that STD system performance is better with query words cut out from continuous speech compared to words recorded in isolated manner. This performance difference can be accounted for large temporal variations
