Best practice TTS based on BERT and VITS with some Natural Speech Features Of Microsoft

这是一个用于TTS算法学习的项目，如果您在寻找直接用于生产的TTS，本项目可能不适合您！

vits_bert.mp4

Based on BERT, NaturalSpeech, VITS

Features

1, Hidden prosody embedding from BERT，get natural pauses in grammar

2, Infer loss from NaturalSpeech，get less sound error

3, Framework of VITS，get high audio quality

💗💗💗Tip: It is recommended to use Infer Loss fine-tune model after base model trained, and freeze PosteriorEncoder during fine-tuning.

Online demo

https://huggingface.co/spaces/maxmax20160403/vits_chinese

Install

pip install -r requirements.txt

cd monotonic_align

python setup.py build_ext --inplace

Infer with Pretrained model

BaiduYun: https://pan.baidu.com/s/1Cj4MnwFyZ0XZmTR6EpygbQ?pwd=yn60

Google: https://drive.google.com/drive/folders/1sioiNpebOLyCmHURgOgJ7ppWI7b-7Rb5?usp=sharing

Or get from release page

put prosody_model.pt To ./bert/prosody_model.pt

put vits_bert_model.pth To ./vits_bert_model.pth

python vits_infer.py --config ./configs/bert_vits.json --model vits_bert_model.pth

./vits_infer_out have the waves infered, listen !!!

Infer with chunk wave streaming out

as key paramter, hop_frame = ∑decoder.ups.padding

python vits_infer_stream.py --config ./configs/bert_vits.json --model vits_bert_model.pth

Text normlize

pip install WeTextProcessing

from tn.chinese.normalizer import Normalizer

normalizer = Normalizer()

...

item = fo.readline().strip()

item = normalizer.normalize(item)

Train

download baker data: https://www.data-baker.com/data/index/TNtts/

change sample rate of waves to 16kHz, and put waves to ./data/waves

put 000001-010000.txt to ./data/000001-010000.txt

python vits_prepare.py -c ./configs/bert_vits.json

python train.py -c configs/bert_vits.json -m bert_vits

Model compression based on knowledge distillation

Student model has 53M size and 3× speed of teacher model.

To train:

python train.py -c configs/bert_vits_student.json -m bert_vits_student

To infer, get studet model at release page or

Google: :https://drive.google.com/file/d/1hTLWYEKH4GV9mQltrMyr3k2UKUo4chdp/view?usp=sharing

python vits_infer.py --config ./configs/bert_vits_student.json --model vits_bert_student.pth

You can use vits_istft as a student model too.

https://github.com/PlayVoice/vits_chinese/tree/vits_istft

Video text

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