Iterative Pseudo-Labeling for Speech Recognition

Benchmark Model Rank Results
speech-recognition-on-librispeech-test-otherConv + Transformer AM + Iterative Pseudo-Labeling (n-gram LM + Transformer Rescoring)#60Word Error Rate (WER): 3.83
speech-recognition-on-librispeech-test-cleanConv + Transformer AM + Iterative Pseudo-Labeling (n-gram LM + Transformer Rescoring)#84Word Error Rate (WER): 2.10