From 688af111556b39d5f105870a1f292190396fb6b2 Mon Sep 17 00:00:00 2001 From: jik876 Date: Fri, 30 Oct 2020 15:11:59 +0900 Subject: [PATCH] Fine-Tuning section added. --- README.md | 28 ++++++++++++++++++++++------ 1 file changed, 22 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 6ae69bf8a..6733af46a 100644 --- a/README.md +++ b/README.md @@ -58,12 +58,28 @@ Details of each folder are as in follows: |UNIVERSAL_V1|V1|Universal|No| +## Fine-Tuning +1. Generate mel-spectrograms in numpy format using [Tacotron2](https://github.com/NVIDIA/tacotron2) with teacher-forcing.
+The file name of the generated mel-spectrogram should match the audio file and the extension should be `.npy`.
+Example: + ``` + Audio File : LJ001-0001.wav + Mel-Spectrogram File : LJ001-0001.npy + ``` +2. Create `ft_dataset` folder and copy the generated mel-spectrogram files into it.
+3. Run the following command. + ``` + python train.py --fine_tuning True --config config_v1.json + ``` + For other command line options, please refer to the training section. + + ## Inference from wav file 1. Make `test_files` directory and copy wav files into the directory. 2. Run the following command. -``` -python inference.py --checkpoint_file [generator checkpoint file path] -``` + ``` + python inference.py --checkpoint_file [generator checkpoint file path] + ``` Generated wav files are saved in `generated_files` by default.
You can change the path by adding `--output_dir` option. @@ -73,9 +89,9 @@ You can change the path by adding `--output_dir` option. You can generate mel-spectrograms using [Tacotron2](https://github.com/NVIDIA/tacotron2), [Glow-TTS](https://github.com/jaywalnut310/glow-tts) and so forth. 2. Run the following command. -``` -python inference_e2e.py --checkpoint_file [generator checkpoint file path] -``` + ``` + python inference_e2e.py --checkpoint_file [generator checkpoint file path] + ``` Generated wav files are saved in `generated_files_from_mel` by default.
You can change the path by adding `--output_dir` option.