Live Demonstration: Real-Time Spoken Digit Recognition using the DeltaRNN Accelerator

This demonstration shows a real-time continuous speech recognition hardware system using our previously published DeltaRNN accelerator that enables low latency recurrent neural network (RNN) computation. The network is trained on augmented audio samples from the TIDIGITS dataset to achieve a label error rate (LER) of 2.31%. It is implemented on a Xilinx Zynq-7100 FPGA running at 1 MHz. The incremental RNN power consumption is 30 mW. Visitors interact with the system by speaking digits into a microphone connected to the FPGA system and the classification outputs of the network are continuously displayed on a laptop screen in real time.