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aims to generate english-complatible dataset since no FR alphabet.txt for now see https://github.com/mozilla/DeepSpeech/pull/1599#issuecomment-426544379 for more info |
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| .. | ||
| benchmark_nc.py | ||
| benchmark_plotter.py | ||
| gpu_usage_chart | ||
| gpu_usage_plot | ||
| graphdef_binary_to_text.py | ||
| import_cv.py | ||
| import_fisher.py | ||
| import_ldc93s1.py | ||
| import_librivox.py | ||
| import_swb.py | ||
| import_ted.py | ||
| import_timit.py | ||
| import_ts.py | ||
| import_voxforge.py | ||
| job-template.sbatch | ||
| ops_in_graph.py | ||
| README.md | ||
| run-cluster.sh | ||
| run-ldc93s1.sh | ||
| run-tc-ldc93s1_frozen.sh | ||
| run-tc-ldc93s1_new.sh | ||
| run-tc-ldc93s1_singleshotinference.sh | ||
Utility scripts
This folder contains scripts that can be used to do training on the various included importers from the command line. This is useful to be able to run training without a browser open, or unattended on a remote machine. They should be run from the base directory of the repository. Note that the default settings assume a very well-specified machine. In the situation that out-of-memory errors occur, you may find decreasing the values of --train_batch_size, --dev_batch_size and --test_batch_size will allow you to continue, at the expense of speed.