DRAGON Systems Resource Management Benchmark Results February 1991

In this paper we present preliminary results obtained at Dragon Systems on the Resource Maaaagernent benchmark task. The basic conceptual units of our system are Phonemes-m-Context (PICs), which are represented a s Hidden Mmkov Models, each of which is eapressed as a sequence of Phonetic Elements (PELs). The PELs corresponding to a given phoneme constitute a kind of alphabet for the representation of PICs. For the speaker-dependent tests, two basic methods of training the acoustic models were investigated. 'nac first method of training the Resouro~ Managemera models is to ~e-estimate the models for each test speaker from that speaker's training data, keeping the PEL spellings of the PICs fixed. The second approach is to use the re-estimated models from the first melhod to derive a segmentation of the training data, then to respall the PICs in a hrgely speaker-depmdmt manner in order to improve the representation of speaker differences. A full explanation of these methods is given, as are results using each method. In addition to repotting on two different training slrategies, we disoass NBest results. The N-Best algorithm is a modification of the algorithm proposed by Soong and Huang at the Jtme 1990 workshop. This algorithm runs as a post-processing step and uses an A*-search (an algorithm also known as a 'stack decoder').