OlaWod / my-fastspeech2

my-fastspeech2

Usage

LJSpeech

prepare_data:

python prepare_data.py config/LJSpeech/preprocess.yaml

mfa:

./mfa/montreal-forced-aligner/bin/mfa_align ./preprocessed_data/LJSpeech/data ./mytext/lexicon/librispeech-lexicon.txt english ./preprocessed_data/LJSpeech/textgrid

preprocess:

python preprocess.py config/LJSpeech/preprocess.yaml

train:

python train.py -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml

evaluate:

python evaluate.py -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml

synthesize:

python synthesize.py --source test-en.txt --restore_step 100000 -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml

AISHELL3

prepare_data:

python prepare_data.py config/AISHELL3/preprocess.yaml

mfa:

./mfa/montreal-forced-aligner/bin/mfa_train_and_align ./preprocessed_data/AISHELL3/data ./mytext/lexicon/pinyin-lexicon-r.txt ./preprocessed_data/AISHELL3/textgrid

preprocess:

python preprocess.py config/AISHELL3/preprocess.yaml

train:

python train.py -p config/AISHELL3/preprocess.yaml -m config/AISHELL3/model.yaml -t config/AISHELL3/train.yaml

evaluate:

python evaluate.py -p config/AISHELL3/preprocess.yaml -m config/AISHELL3/model.yaml -t config/AISHELL3/train.yaml

synthesize:

python synthesize.py --source test.txt --restore_step 3000 -p config/AISHELL3/preprocess.yaml -m config/AISHELL3/model.yaml -t config/AISHELL3/train.yaml

Reference

https://arxiv.org/abs/2006.04558

https://github.com/ming024/FastSpeech2