TheAthleticCoder / HiPAMA_Replicate

This repository is the implementation of the HiPAMA architecture, introduced in the paper, Hierarchical Pronunciation Assessment with Multi-Aspect Attention (ICASSP 2023).

HiPAMA

This repository is the implementation of the paper, Hierarchical Pronunciation Assessment with Multi-Aspect Attention (ICASSP 2023).

Our code is based on the open source, https://github.com/YuanGongND/gopt (Gong et al, 2022).

Dataset

An open source dataset, SpeechOcean762 (licenced with CC BY 4.0) is used. You can download it from https://www.openslr.org/101.

Training and Evaluation (HiPAMA)

This bash script will run each model 5 times with ([0, 1, 2, 3, 4]).

• cd src
• bash run_hipama.sh

Note that every run does not produce the same results due to the random elements.

Run baseline (GOPT)

This bash script will run each model 5 times with ([0, 1, 2, 3, 4]).

• cd src
• bash my_run_gopt.sh

Analysis Running

The base code provided is not able to generate results successfully. You can run the code file analysis.py on the exp/ folder which gives the mean, std for phonemes, utterances and words.

Citation

@INPROCEEDINGS{10095733,
  author={Do, Heejin and Kim, Yunsu and Lee, Gary Geunbae},
  booktitle={ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
  title={Hierarchical Pronunciation Assessment with Multi-Aspect Attention}, 
  year={2023},
  volume={},
  number={},
  pages={1-5},
  doi={10.1109/ICASSP49357.2023.10095733}}