Hibiki ASR Phonemizer
This model is a Phoneme Level Speech Recognition network, originally a fine-tuned version of openai/whisper-large-v3 on a mixture of Different Japanese datasets.
it can detect, transcribe and do the following:
- non-speech sounds such as gasp, erotic moans, laughter, etc.
- adding punctuations more faithfully. Don't use this model without the post processing functions I wrote below, or you'll get less than ideal performance. check the notebook.
to reverse the process and get the graphemes, use this model.
How to use
Check here -> Notebook
Intended uses & limitations
No restrictions is imposed by me, but proceed at your own risk, The User (You) are entirely responisble for their actions.
Training and evaluation data
- Japanese Common Voice 17
- ehehe Corpus
- Manually cleaned and annotated custom Game and Anime dataset (around 8 hours)
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Compute and Duration
- 1x A100(40G)
- 64gb RAM
- BF16
- 14hrs
Framework versions
- Transformers 4.41.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Respair/Hibiki_ASR_Phonemizer_v0.2
Base model
openai/whisper-large-v3