1.`--config` is the configuration file to use. The provided configurations can be used directly. And you can change some values in the configuration file and train the model with a different config.
2.`--data` is the path of the LJSpeech dataset, the extracted folder from the downloaded archive (the folder which contains metadata.txt).
3.`--resume` is the path of the checkpoint. If it is provided, the model would load the checkpoint before trainig.
4.`--output` is the directory to save results, all result are saved in this directory. The structure of the output directory is shown below.
-`--config` is the configuration file to use. The provided configurations can be used directly. And you can change some values in the configuration file and train the model with a different config.
-`--data` is the path of the LJSpeech dataset, the extracted folder from the downloaded archive (the folder which contains metadata.txt).
-`--resume` is the path of the checkpoint. If it is provided, the model would load the checkpoint before trainig.
-`--output` is the directory to save results, all result are saved in this directory. The structure of the output directory is shown below.
```text
├── checkpoints # checkpoint
...
...
@@ -53,8 +53,8 @@ optional arguments:
└── log # tensorboard log
```
5.`--device` is the device (gpu id) to use for training. `-1` means CPU.
6.`--wavenet` is the path of the wavenet checkpoint to load. If you do not specify `--resume`, then this must be provided.
-`--device` is the device (gpu id) to use for training. `-1` means CPU.
-`--wavenet` is the path of the wavenet checkpoint to load. If you do not specify `--resume`, then this must be provided.
Before you start training a ClariNet model, you should have trained a WaveNet model with single Gaussian output distribution. Make sure the config of the teacher model matches that of the trained model.
...
...
@@ -90,11 +90,11 @@ optional arguments:
--data DATA path of LJspeech dataset.
```
1.`--config` is the configuration file to use. You should use the same configuration with which you train you model.
2.`--data` is the path of the LJspeech dataset. A dataset is not needed for synthesis, but since the input is mel spectrogram, we need to get mel spectrogram from audio files.
3.`checkpoint` is the checkpoint to load.
4.`output_path` is the directory to save results. The output path contains the generated audio files (`*.wav`).
5.`--device` is the device (gpu id) to use for training. `-1` means CPU.
-`--config` is the configuration file to use. You should use the same configuration with which you train you model.
-`--data` is the path of the LJspeech dataset. A dataset is not needed for synthesis, but since the input is mel spectrogram, we need to get mel spectrogram from audio files.
-`checkpoint` is the checkpoint to load.
-`output_path` is the directory to save results. The output path contains the generated audio files (`*.wav`).
-`--device` is the device (gpu id) to use for training. `-1` means CPU.
