Combining open vocabulary recognition and word confusion networks

A limitation of most speech recognizers is that they only recognize words from a fixed vocabulary. In this paper, we explore a technique for addressing this deficiency using automatically derived units made up of letters and phones. We show how these units can be used for letter-to-phone conversion and open-vocabulary recognition. We further show how these units can be merged to form novel words while maintaining a word lattice structure. This allows creation of a word confusion network containing both in- and out-of-vocabulary (OOV) words. Experiments show these open vocabulary confusion networks improve recognition accuracy. They also allow open vocabulary recognition to be used in concert with a convenient confusion network result representation.