A class of data-flow architectures for speech recognition

The behavior of many speech recognition systems, and of some Artificial Intelligence programs, can he modeled as a data driven computation in which the "instructions" are complex but inexpensive operations (e.g. the evaluation of the likelihood of a partial sentence hypothesis), and the "data-flow graph" is derived directly from the knowledge representation (e.g. the phoneme-level network in a Harpy system). The architecture of a machine that exploits this characteristic is presented together with the results of the simulation of one possible implementation.