Awesome
Yukarin: train the first stage model for voice conversion
This repository is refactoring the training code for the first stage model of Bcome Yukarin: Convert your voice to favorite voice.
Supported environment
- Linux OS
- Python 3.6
Preparation
Installation required libraries
pip install -r requirements.txt
How to run code (preliminary knowledge)
To run a Python script in this repository, you should set the environment variable PYTHONPATH
to find the yukarin
library.
For example, you can run scripts/foo.py
with the following command:
PYTHONPATH=`pwd` python scripts/foo.py
Create dataset
Prepare voice data
Put input/target voice data in two directories (ex. input_wav
and target_wav
).
These data should be same file names.
Create acoustic feature
Create input/target acoustic feature files from each voice data.
python scripts/extract_acoustic_feature.py \
-i './input_wav/*' \
-o './input_feature/'
python scripts/extract_acoustic_feature.py \
-i './target_wav/*' \
-o './target_feature/'
Align data
Align input and target acoustic features in time direction.
In the following example, create the alignment data between input_feature
and target_feature
into aligned_indexes
.
python scripts/extract_align_indexes.py \
-i1 './input_feature/*.npy' \
-i2 './target_feature/*.npy' \
-o './aligned_indexes/'
Calculate frequency statistics
Calculate frequency statistics for input and target voice data. Statistics are needed for voice pitch conversion.
python scripts/extract_f0_statistics.py \
-i './input_feature/*.npy' \
-o './input_statistics.npy'
python scripts/extract_f0_statistics.py \
-i './target_feature/*.npy' \
-o './target_statistics.npy'
Train
Create the training config file config.json
Modify input_glob
, target_glob
and indexes_glob
in sample_config.json
, then can train.
Train
python train.py \
sample_config.json \
./model_stage1/
Test
Put the test input voice data in a directory (ex. test_wav
), and run voice_change.py
.
python scripts/voice_change.py \
--model_dir './model_stage1' \
--config_path './model_stage1/config.json' \
--input_statistics 'input_statistics.npy' \
--target_statistics 'target_statistics.npy' \
--output_sampling_rate 24000 \
--disable_dataset_test \
--test_wave_dir './test_wav/' \
--output_dir './output/'
Advanced: with second stage model
Become Yukarin's Second Stage Model can improve the quality of the converted voice.
Train
Train the second stage model referring to Second Stage Model in Become Yukarin.
Test
Put the test input voice data in a directory (ex. test_wav
), and run voice_change_with_second_stage.py
.
python scripts/voice_change_with_second_stage.py \
--voice_changer_model_dir './model_stage1' \
--voice_changer_config './model_stage1/config.json' \
--super_resolution_model './model_stage2/' \
--super_resolution_config './model_stage2/config.json' \
--input_statistics 'input_statistics.npy' \
--target_statistics 'target_statistics.npy' \
--out_sampling_rate 24000 \
--disable_dataset_test \
--dataset_target_wave_dir '' \
--test_wave_dir './test_wav' \
--output_dir './output/'