Iterative Pseudo-Labeling for Speech Recognition

Benchmark Model Rank Results
speech-recognition-on-librispeech-test-cleanConv + Transformer AM + Iterative Pseudo-Labeling (n-gram LM + Transformer Rescoring)#77Word Error Rate (WER): 2.10
speech-recognition-on-librispeech-test-otherConv + Transformer AM + Iterative Pseudo-Labeling (n-gram LM + Transformer Rescoring)#52Word Error Rate (WER): 3.83