Spoken term detectionfor OOV terms based on phone fragment

In this paper, we focus on the problem of search for Out Of Vocabulary (OOV) in spoken term detection (STD). The phone level fragment is adopted as the speech recognition decoding unit. Furthermore, weop-timize the phone level fragment in speech recognition system by adding word-position marker. Then inverted triphone index is built to implement fuzzy search for OOV terms. In the term detection confidence measure procedure, we present a method based on multi-layer perceptron (MLP) to complement for lattice-based confidence measure. Experimental result indicates that the optimizationof fragment can give a 3% relative increase in Actual Term Weighted Value (ATWV) for OOV terms. The confidence measure based on MLP could provide another relativeimprovement of 5.5% in ATWV.