Spoken term detection using multiple speech recognizers’ outputs at NTCIR-9 SpokenDoc STD subtask

This paper describes spoken term detection (STD) with false detection control using a phoneme transition network (PTN) derived from multiple speech recognizers ’ outputs at NTCIR-9 SpokenDoc STD subtask. Using the output of multiple speech recognizers, the PTN method is effective at correctly detecting out-of-vocabulary (OOV) terms and is robust to certain recognition errors. However, it exhibits a high false detection rate. Therefore, we applied two false detection control parameters to the search engine that accepts the PTN-formed index. One of the parameters is based on the consept of the majority voting scheme, and the other is a measure of ambiguity in confusion networks (CN). These parameters improve the STD performance (F-measure value of 0.725) compared to that without any parameters (F-measure value of 0.714)