Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition
Table 3: Compare with other models in performance and real-time factor.
['[BOLD] Model', '[BOLD] DEV', '[BOLD] TEST', '[BOLD] RTF']
From another perspective, the ST-NAT has the fastest inference speed among them, which is only about 1/10 of speech-transformer. The ST-NAT with a transformer language model can achieve the best CER of 7.02% on the test set and an RTF of 0.0292.