diff options
| author | Jan Buethe <jbuethe@amazon.de> | 2023-10-19 22:45:45 +0300 |
|---|---|---|
| committer | Jan Buethe <jbuethe@amazon.de> | 2023-10-19 22:45:45 +0300 |
| commit | 2192e85b91eca441465ce523162076733584b004 (patch) | |
| tree | 08536e903737f3b601554fd40f3b7996584534dd | |
| parent | 055c6830189acf0d95422d16bf457344b13b819d (diff) | |
restructured osce readme
| -rw-r--r-- | dnn/torch/osce/README.md | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/dnn/torch/osce/README.md b/dnn/torch/osce/README.md index b3a58655..74d1f505 100644 --- a/dnn/torch/osce/README.md +++ b/dnn/torch/osce/README.md @@ -26,14 +26,6 @@ Second step is to run a patched version of opus_demo in the dataset folder, whic The argument to -silk_random_switching specifies the number of frames after which parameters are switched randomly. -## Generating inference data -Generating inference data is analogous to generating training data. Given an item 'item1.wav' run -`mkdir item1.se && sox item1.wav -r 16000 -e signed-integer -b 16 item1.raw && cd item1.se && <path_to_patched_opus_demo>/opus_demo voip 16000 1 <bitrate> ../item1.raw noisy.s16` - -The folder item1.se then serves as input for the test_model.py script or for the --testdata argument of train_model.py resp. adv_train_model.py - -Checkpoints of pre-trained models are located here https://media.xiph.org/lpcnet/models/lace-20231019.tar.gz. - ## Regression loss based training Create a default setup for LACE or NoLACE via @@ -62,4 +54,12 @@ for running the training script in foreground or `nohup python adv_train_model.py nolace_adv.yml <output folder> &` -to run it in background. In the latter case the output is written to `<output folder>/out.txt`.
\ No newline at end of file +to run it in background. In the latter case the output is written to `<output folder>/out.txt`. + +## Inference +Generating inference data is analogous to generating training data. Given an item 'item1.wav' run +`mkdir item1.se && sox item1.wav -r 16000 -e signed-integer -b 16 item1.raw && cd item1.se && <path_to_patched_opus_demo>/opus_demo voip 16000 1 <bitrate> ../item1.raw noisy.s16` + +The folder item1.se then serves as input for the test_model.py script or for the --testdata argument of train_model.py resp. adv_train_model.py + +Checkpoints of pre-trained models are located here: https://media.xiph.org/lpcnet/models/lace-20231019.tar.gz
\ No newline at end of file |