Research and Development of SNAP: Semantic Network Array Processor

这是卡内基梅隆大学和南加州大学联合项目的一部分，该项目旨在构建一个大规模并行处理器，并将其用于自然语言翻译。要构建的系统是一组定制处理器，专门用于语义网络中的标记传递。该项目的一个具体目标是实现一个实时语音到语音对话翻译系统，其词汇量约为500个单词。这个系统必须包含自然语言理解和生成组件。这个项目的最终成果将是一个包含16384个语义网络节点的阵列，以及实现翻译系统的软件。

This is part of a joint project at Carnegie Mellon University and the University of Southern California to build a massively parallel processor and use it for natural language translation. The system to be built is an array of custom processors that are specialized for marker passing in semantic networks. A specific goal of this project is to implement a real-time speech-to-speech dialogue translation system with about 500 words in its vocabulary. This system will necessarily include natural language understanding and generation components. The culmination of this project will be an array of 16,384 semantic network nodes with software implementing the translation system.