Within a spoken term detection (STD) system, the decision maker plays an important role in retrieving reliable detections. Most of the state-of-the-art STD systems make decisions based on a confidence measure that is term-independent, which poses a serious problem for out-of-vocabulary (OOV) term detection. In this paper, we study a term-dependent confidence measure based on confidence normalisation and discriminative modelling, particularly focusing on its remarkable effectiveness for detecting OOV terms. Experimental results indicate that the term-dependent confidence provides much more significant improvement for OOV terms than terms in-vocabulary.
Bibliographic reference. Wang, Dong / King, Simon / Frankel, Joe / Bell, Peter (2009): "Term-dependent confidence for out-of-vocabulary term detection", In INTERSPEECH-2009, 2139-2142.