This repo is the code base of "Improving the Goodness of Pronunciation score by using Deep Neural Networks: Single-input Classification and Sequence-to-Sequence Classification" (2018).

The OHSU Child Corpus is not included.

1. Results
2. features_assembly
3. force_alignment
4. result_recording
5. src
6. utils
7. External: HoldDir

holds AE_phones(AutoEncoder) and CDNN_phones(Convolutional & Deep Neural Networks). These two folders hold the saved results from training and testing DNN in the form of Pickled Python Dictionaries.

contains scripts for creating train and test folders from the Childs' corpus.

holds the Montreal Forced Aligner(MFA) scripts, custom feature_assembly scripts for MFA use, and alignment evaluation.

uses Results to sort and print results, plot results, or create sorted csv results for LaTex tables.

contains scripts for creating, training, and testing Neural Network architectures on specified features and sbatch scripts for running on slurm cluster. NOTE: to save Train and Test directories you'll need to setup a "HoldDir" (Hold directory) somewhere on you computer and link in the script file appropriately.

contains additional scripts, such as generators for training, model saving/loading/weight transfer, and attention decoder

holds Train & Test directories to prevent having to . them with git repeatedly