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Parallel system design for time-delay neural networks

The authors 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.