Rejection for connected digit recognition based on GPD segmental discrimination

Connected digit recognition is an area that has attracted significant attention because of its importance in automating a wide range of applications. In an actual application, the performance of the connected digit recognizer must be measured along two dimensions: its recognition accuracy over connected digit strings, and its rejection rate over utterances with no digits. This paper presents a rejection method for connected digit recognition. This rejection method is a post-processor to an HMM-based recognizer and consists of two stages: a digit/non-digit classification stage, and a string verification stage. The digit/non-digit classifier is discriminatively trained to determine if a given digit segment in the recognized string actually contains a digit. The string verification stage combines the results of the digit/non-digit classifier to make the final rejection decision. Experimental results on two independent databases, show that this rejection method is successful in not only rejecting speech with no connected digits, but also in rejecting putative errors, which would have resulted in misrecognition