Evaluation of Fast Spoken Term Detection Using a Suffix Array

We previously proposed [1] fast spoken term detection that uses a suffix array as a data structure for searching a largescale speech documents. In this method, a keyword is divided into sub-keywords, and the phoneme sequences that contain two or more sub-keywords are output as results. Although the search is executed very quickly on a 10,000-h speech database, we only proposed a variety of matching procedures in [1]. In this paper, we compare different varieties of matching procedures in which the number of phonemes in a subkeyword and the required number of sub-keywords to be contained in a search result are different. We also compare the performance and the process time of our method with typical spoken term detection using an inverted index.