Speech recognition for DARPA communicator

Abstract

We report the results of investigations in acoustic modeling, language modeling and decoding techniques, for DARPA Communicator, a speaker-independent, telephone-based dialog system. By a combination of methods, including enlarging the acoustic model, augmenting the recognizer vocabulary, conditioning the language model upon dialog state, and applying a post-processing decoding method, we lowered the overall word error rate from 21.9% to 15.0%, a gain of 6.9 absolute and 31.5% relative.