Increasing interest is being shown in the use of Java for large scale or Grande applications. This new use of Java places specific demands on the Java execution environments that can be tested using the Java Grande benchmark suite [5], [6], [7]. The large processing requirements of Grande applications makes parallelisation of interest. A suite of parallel benchmarks has been developed from the serial Java Grande benchmark suite, using three parallel programming models: Java native threads, MPJ (a message passing interface) and JOMP (a set of OpenMP-like directives). The contents of the suite are described, and results presented for a number of platforms.

Increasing interest is being shown in the use of Java for large scale or Grande applications. This new use of Java places specific demands on the Java execution environments that could be tested and compared using a standard benchmark suite. We describe the design and implementation of such a suite, paying particular attention to Java-specific issues. Sample results are presented for a number of implementations of the Java Virtual Machine (JVM). Copyright © 2000 John Wiley & Sons, Ltd.

Two methods of adapting speech recognition templates for developing multispeaker or speaker-independent vocabularies are tested. Both methods rely on feedback to assess the accuracy of recognition, and both use the test utterance to modify the correct template when recognition fails. In addition, one method uses the test utterance to modify intruding templates, moving them away from the test token's position in pattern space; this method is more effective for developing both multispeaker and speaker-independent vocabularies.>