wav2vec2-xls-r-300m_phoneme-mfa_korean
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on a phonetically balanced native Korean read-speech corpus.
- Model Management by: excalibur12
Training and Evaluation Data
Training Data
- Data Name: Phonetically Balanced Native Korean Read-speech Corpus
- Num. of Samples: 54,000 (540 speakers)
- Audio Length: 108 Hours
Evaluation Data
- Data Name: Phonetically Balanced Native Korean Read-speech Corpus
- Num. of Samples: 6,000 (60 speakers)
- Audio Length: 12 Hours
Training Hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 20 (EarlyStopping: patience: 5 epochs max)
- mixed_precision_training: Native AMP
Evaluation Results
- Phone Error Rate 3.88%
- Monophthong-wise Error Rates: (To be posted)
Output Examples
MFA-IPA Phoneset Tables
Vowels
Consonants
Experimental Results
Official implementation of the paper (ICPhS 2023)
Major error patterns of L2 Korean speech from five different L1s: Chinese (ZH), Vietnamese (VI), Japanese (JP), Thai (TH), English (EN)
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1