Before revision:  In this work, we propose an end-to-end model for the low-resource speech recognition, which fuses a pre-trained audio encoder (wav2vec2.0) and a pre-trained text decoder (BERT) .
After revision:  In this work, we propose an end-to-end model for the low-resource speech recognition, which fuses a pre-trained audio encoder (wav2vec2.0) and a pre-trained linguistic encoder (BERT) .