Parallel system design for time-delay neural networks

摘要

In this paper, we develop a parallel structure for the time-delay neural network used in some speech recognition applications. The effectiveness of the design is illustrated by 1) extracting a window computing model from the time-delay neural systems; 2) building its pipelined architecture with parallel or serial processing stages; and 3) applying this parallel window computing to some typical speech recognition systems. An analysis of the complexity of the proposed design shows a greatly reduced complexity while maintaining a high throughput rate.