Vocabulary-independent word confidence measure using subword features
Jiang Li, Xuedong Huang · 1998
This paper discusses how to compute word-level confidence measures based on sub-word features for large-vocabulary speaker-independent speech recognition. The performance of confidence measure using features at word, phone and senone level is experimentally studied. A framework of transformation function based system using sub-word features is proposed for high performance confidence estimation. In this system, discriminative training is used to optimize the parameters of the transformation function. In comparison to the baseline, experiments show that the proposed system reduces the equal error rate by 15%, with up to 40% false acceptance error reduction at various fixed false rejection rate. The combination of multiple features under the proposed framework is also discussed.