Abstract A real‐time prototype speech recognizer has been implemented on a 66‐processor distributed‐memory parallel computer. Simple phrases are recognized in approximately 4 to 10 seconds. Scalability, performance and flexibility are the three main aims of this implementation, the ultimate goal being to construct a large vocabulary speech recognizer which responds quickly. A set of three techniques is investigated in this implementation: asynchronous methodology to minimize synchronization overheads, distributed control to avoid a central communications bottleneck, and dynamic load balancing to provide a flexible response to an unpredictable computational load. The effect on memory, processor time allocation and communications is observed in real‐time using hardware monitoring aids.

Four types of neural networks which have previously been established for speech recognition and tested on a small, seven-speaker, 100-sentence database are applied to the TIMIT database. The networks are a recurrent network phoneme recognizer, a modified Kanerva model morph recognizer, a compositional representation phoneme-to-word recognizer, and a modified Kanerva model morph-to-word recognizer. The major result is for the recurrent net, giving a phoneme recognition accuracy of 57% from the si and sx sentences. The Kanerva morph recognizer achieves 66.2% accuracy for a small subset of the sa and sx sentences. The results for the word recognizers are incomplete.>

An integrated system which is part of a larger project in robotic assembly is described in terms first of its separate components and then of its integrated form and performance. The parts to be assembled are previously designed by CAD, and therefore geometrical models of the parts are available in a solid modeler which is incorporated in the system. In the integrated system presented, simplified versions of the component parts of an aircraft equipment tray are recognized and located by vision from an arbitrary initial state and moved to a final state appropriate to assembly. The components of the system described are: low-level vision processing using a transputer array; an intelligent vision system integrated with a solid modeler for part recognition and location; a path planner using 2/sup n/-array tree search; and the control of a PUMA robot. The integration of the components and the performance of the prototype system are described.>