Term-Dependent Confidence for Out-of-Vocabulary Term Detection

Dong Wang, Simon King, Joe Frankel, Peter Bell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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.
Original languageEnglish
Title of host publicationIn Proc. Interspeech
Publication statusPublished - 2009


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