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* init Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * renamed file Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * adding all cleaning scripts Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * skip sentence if error Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove I-SAME Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * fix tyle Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove I the first from training Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove DM and Da from upsampling Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove I -> one/first, also add space around dash for alphanumerical context, remove rare currency from being upsampled Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove dalton and DM from being verbalized Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * remove Da and DM sentences competely Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * addressed review feedback, added data folder in examples Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * refactored code, added data utils functions Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * fix lgtm Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * fix lgtm Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * added electronic wfst for english neural TN Signed-off-by: Yang Zhang <yangzhang@nvidia.com> * header and lgtm Signed-off-by: Yang Zhang <yangzhang@nvidia.com> |
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| .. | ||
| en | ||
| ru | ||
| __init__.py | ||
| data_loader_utils.py | ||
| normalize.py | ||
| normalize_with_audio.py | ||
| README.md | ||
| run_evaluate.py | ||
| run_predict.py | ||
| token_parser.py | ||
Text Normalization system for english, e.g. 123 kg -> one hundred twenty three kilograms
Offers prediction and evaluation on text normalization data, e.g. Google text normalization dataset.
Install dependencies: bash ../setup.sh
Example prediction run:
python run_predict.py --input=INPUT_FILE --output=OUTPUT_FILE [--verbose]
Example evaluation run:
python run_evaluate.py --input=./en_with_types/output-00001-of-00100 [--cat CATEGORY]