This model is Wav2Vec2-Large-XLSR-53
fine-tuned on the manually annotated subset of
CMU's L2-Arctic dataset. It was fine-tuned
to perform automatic phonetic transcriptions in IPA.
It was tuned following a similar procedure as described
by vitouphy
with the TIMIT dataset.
Usage
To use the model, create a pipeline and invoke it with
the path to your WAV, which must be sampled at 16KHz.
The manually annotated subset of L2-Arctic was divided
into training and testing datasets with a 90/10 split.
The performance metrics for the testing dataset are
included below.
WER - 0.425
CER - 0.128
Citation
If you find our model helpful, please feel free to cite us.
@article{Bo_Rubino_Xu_2024,
title={A Mispronunciation-Based Voice-Omics Representation Framework for Screening Specific Language Impairments in Children},
DOI={10.1109/ichi61247.2024.00045},
journal={2024 IEEE 12th International Conference on Healthcare Informatics (ICHI)},
author={Bo, Wei and Rubino, Matthew and Xu, Wenyao},
year={2024},
month={Jun},
pages={294–304}
}
