Acoustic modeling of subword units for speech recognition

Acoustic modeling method of basic speech subword units are discussed to provide high word recognition accuracy. It is shown that for a basic set of 47 context-independent phone-like units, word accuracies on the order of 86-90% can be obtained for a 1000-word vocabulary, in a speaker-independent mode, for a grammar with a perplexity of 60, on independent test sets. When the basic set of units is increased to include context-dependent units, word recognition accuracies of from 91 to 93% can be achieved on the same test sets. Based on outside results and some of the present ones, it is possible to increase word recognition accuracies by about 2-3% using known modeling techniques