“A Full Text-Dependent End to End Mispronunciation Detection and Diagnosis with Easy Data Augment Techniques“ https://arxiv.org/pdf/2104.08428.pdf

Implemented with TIMIT and L2-Arctic Database:

TIMIT : -
L2-Arctic: (https://psi.engr.tamu.edu/l2-arctic-corpus/)

Note:
CNN-RNN-CTC is baseline.
attention_aug is our best system.

Usage:

1. Just need to change your kaldi_path in path.sh and your data_path in run.sh
2. ./run.sh to get the decode sequence (decode_seq)
3. mv decode_seq ./result/hyp ./mdd_result.sh

Next step: We will update the results on large datasets (such as Librispeech)