A Segment-Based Wordspotter Using Phonetic Filler Models
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
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In this article we present a novel approach to reference verification, the problem of determining if a speakers utterance matches a specific reference (text) string. We will then discuss its application to a reading tracker system for childrens speech. Unlike other reading tracker systems proposed in the literature, that are built over conventional speech recognizers with ad-hoc language models, the reading tracker described here is designed specifically for the task of estimating whether a child has read an expected sequence of words out loud. The tracker is designed to handle in a natural and flexible way the disfluencies that frequently appear in childrens speech while reading out loud, (e.g., partial-words, repetitions, self-corrections, sentence-restarts, etc), and to overcome problems caused by using language models within the reference verification task. Three mechanisms have been introduced for this purpose: the utilization of filler models and the inclusion of forward and backward inter-word transitions in the static decoding network. While this article focuses on the approach used to overcome errors observed in previous systems, the performance of this system will be evaluated on a corpus of childrens speech while reading out loud and compared to the performance of a traditional reading tracker system that is built on top of a speech recognition system. The results of this comparison will be presented at WOCCI 2009.