| # ASR project barebones |
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| ## Installation guide |
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| 1. `pip install -r ./requirements.txt` |
| 2. Download from http://www.openslr.org/11/ `3-gram.arpa.gz` and `librispeech-vocab.txt` |
| 3. `python hw_asr/text_encoder/fix_vocab.py` and `python hw_asr/text_encoder/lower_model.py` to prepare vocab and model for using |
| 4. If you want to test my model, download it from the https://drive.google.com/file/d/1QrSsx56V5YNjGHUBWy6CIRVbNbjKWUpJ/view?usp=share_link , name it `checkpoint.pth` and place to the directory `default_test_model/` |
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| ## Train |
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| 1. `python train.py --config hw_asr/configs/config2.json` |
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| ## Test |
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| 1. `python test.py -c default_test_config.json -r default_test_model/checkpoint.pth` |
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| ## Wandb report |
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| 1. You can check my wandb report (only on Russian) and wandb project from the https://wandb.ai/tgritsaev/asr_project/reports/DLA-HW-1--Vmlldzo1NzY3NjA5?accessToken=kotkj5oyzomf2d2g1f40mczdnpirwvuw1f538zx9k491g1cfh3wg9iwhsb65o054 |
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