After Width: | Height: | Size: 441 KiB |
@ -0,0 +1,13 @@
|
||||
#!/bin/bash
|
||||
export MAIN_ROOT=`realpath ${PWD}/../../`
|
||||
|
||||
export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
|
||||
export LC_ALL=C
|
||||
|
||||
export PYTHONDONTWRITEBYTECODE=1
|
||||
# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
|
||||
export PYTHONIOENCODING=UTF-8
|
||||
export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH}
|
||||
|
||||
MODEL=fastspeech2
|
||||
export BIN_DIR=${MAIN_ROOT}/paddlespeech/t2s/exps/${MODEL}
|
@ -0,0 +1,61 @@
|
||||
#!/bin/bash
|
||||
source path.sh
|
||||
|
||||
gpus=0
|
||||
stage=0
|
||||
stop_stage=100
|
||||
|
||||
# with the following command, you can choice the stage range you want to run
|
||||
# such as `./run.sh --stage 0 --stop-stage 0`
|
||||
# this can not be mixed use with `$1`, `$2` ...
|
||||
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
|
||||
|
||||
mkdir download
|
||||
|
||||
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
||||
# install PaddleGAN
|
||||
git clone https://github.com/PaddlePaddle/PaddleGAN.git
|
||||
pip install -e PaddleGAN/
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
|
||||
# download pretrained PaddleGAN model
|
||||
wget -P download https://paddlegan.bj.bcebos.com/models/wav2lip_hq.pdparams
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
|
||||
# download pretrained tts models and unzip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip
|
||||
unzip -d download download/pwg_baker_ckpt_0.4.zip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
unzip -d download download/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
|
||||
# run tts
|
||||
CUDA_VISIBLE_DEVICES=${gpus} \
|
||||
python3 ${BIN_DIR}/synthesize_e2e.py \
|
||||
--fastspeech2-config=download/fastspeech2_nosil_baker_ckpt_0.4/default.yaml \
|
||||
--fastspeech2-checkpoint=download/fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \
|
||||
--fastspeech2-stat=download/fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \
|
||||
--pwg-config=download/pwg_baker_ckpt_0.4/pwg_default.yaml \
|
||||
--pwg-checkpoint=download/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \
|
||||
--pwg-stat=download/pwg_baker_ckpt_0.4/pwg_stats.npy \
|
||||
--text=sentences.txt \
|
||||
--output-dir=output/wavs \
|
||||
--inference-dir=output/inference \
|
||||
--phones-dict=download/fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt
|
||||
# output/inference is not needed here, which save the static models
|
||||
rm -rf output/inference
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
|
||||
# We only test one audio here, cause it's slow
|
||||
CUDA_VISIBLE_DEVICES=${gpus} \
|
||||
python3 PaddleGAN/applications/tools/wav2lip.py \
|
||||
--checkpoint_path download/wav2lip_hq.pdparams \
|
||||
--face Lamarr.png \
|
||||
--audio output/wavs/000.wav \
|
||||
--outfile output/tts_lips.mp4 \
|
||||
--face_enhancement
|
||||
fi
|
@ -0,0 +1 @@
|
||||
000 谁知青蛙一落地,竟变成了一位英俊的王子。于是遵照国王的意思,他做了公主的亲密伴侣。
|
After Width: | Height: | Size: 1.5 MiB |
@ -0,0 +1,74 @@
|
||||
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import argparse
|
||||
import os
|
||||
import re
|
||||
from pathlib import Path
|
||||
|
||||
import paddle
|
||||
from paddleocr import draw_ocr
|
||||
from paddleocr import PaddleOCR
|
||||
from PIL import Image
|
||||
|
||||
|
||||
def evaluate(args, ocr):
|
||||
img_dir = Path(args.img_dir)
|
||||
output_dir = Path(args.output_dir)
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
img_out_dir = output_dir / "imgs"
|
||||
img_out_dir.mkdir(parents=True, exist_ok=True)
|
||||
with open(output_dir / "sentences.txt", "w") as wf:
|
||||
for name in os.listdir(img_dir):
|
||||
id = name.split(".")[0]
|
||||
img_path = img_dir / name
|
||||
result = ocr.ocr(str(img_path), cls=True)
|
||||
# draw result
|
||||
image = Image.open(img_path).convert('RGB')
|
||||
boxes = [line[0] for line in result]
|
||||
txts = [line[1][0] for line in result]
|
||||
scores = [line[1][1] for line in result]
|
||||
im_show = draw_ocr(
|
||||
image, boxes, txts, scores, font_path=args.font_path)
|
||||
im_show = Image.fromarray(im_show)
|
||||
paragraph = "".join(txts)
|
||||
# 过滤出中文结果
|
||||
pattern = re.compile(r'[^(\u4e00-\u9fa5)+,。?、]')
|
||||
sentence = re.sub(pattern, '', paragraph)
|
||||
im_show.save(img_out_dir / name)
|
||||
wf.write(id + " " + sentence + "\n")
|
||||
|
||||
|
||||
def main():
|
||||
# parse args and config and redirect to train_sp
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Synthesize with fastspeech2 & parallel wavegan.")
|
||||
parser.add_argument("--img-dir", default="imgs", type=str, help="img_dir.")
|
||||
parser.add_argument(
|
||||
"--output-dir",
|
||||
type=str,
|
||||
default="output",
|
||||
help="output sentences path.")
|
||||
parser.add_argument(
|
||||
"--font-path", type=str, default="simfang.ttf", help="font path")
|
||||
args = parser.parse_args()
|
||||
|
||||
paddle.set_device("gpu")
|
||||
# need to run only once to download and load model into memory
|
||||
ocr = PaddleOCR(use_angle_cls=True, lang='ch')
|
||||
|
||||
evaluate(args, ocr)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
@ -0,0 +1,13 @@
|
||||
#!/bin/bash
|
||||
export MAIN_ROOT=`realpath ${PWD}/../../`
|
||||
|
||||
export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
|
||||
export LC_ALL=C
|
||||
|
||||
export PYTHONDONTWRITEBYTECODE=1
|
||||
# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
|
||||
export PYTHONIOENCODING=UTF-8
|
||||
export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH}
|
||||
|
||||
MODEL=fastspeech2
|
||||
export BIN_DIR=${MAIN_ROOT}/paddlespeech/t2s/exps/${MODEL}
|
@ -0,0 +1,50 @@
|
||||
#!/bin/bash
|
||||
source path.sh
|
||||
|
||||
gpus=0
|
||||
stage=0
|
||||
stop_stage=100
|
||||
|
||||
# with the following command, you can choice the stage range you want to run
|
||||
# such as `./run.sh --stage 0 --stop-stage 0`
|
||||
# this can not be mixed use with `$1`, `$2` ...
|
||||
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
|
||||
|
||||
mkdir download
|
||||
|
||||
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
||||
# install PaddleOCR
|
||||
pip install "paddleocr>=2.0.1"
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
|
||||
# download pretrained tts models and unzip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip
|
||||
unzip -d download download/pwg_baker_ckpt_0.4.zip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
unzip -d download download/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
|
||||
# run ocr
|
||||
CUDA_VISIBLE_DEVICES=${gpus} \
|
||||
python3 ocr.py --img-dir=imgs --output-dir=output --font-path=simfang.ttf
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
|
||||
# run tts
|
||||
CUDA_VISIBLE_DEVICES=${gpus} \
|
||||
python3 ${BIN_DIR}/synthesize_e2e.py \
|
||||
--fastspeech2-config=download/fastspeech2_nosil_baker_ckpt_0.4/default.yaml \
|
||||
--fastspeech2-checkpoint=download/fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \
|
||||
--fastspeech2-stat=download/fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \
|
||||
--pwg-config=download/pwg_baker_ckpt_0.4/pwg_default.yaml \
|
||||
--pwg-checkpoint=download/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \
|
||||
--pwg-stat=download/pwg_baker_ckpt_0.4/pwg_stats.npy \
|
||||
--text=output/sentences.txt \
|
||||
--output-dir=output/wavs \
|
||||
--inference-dir=output/inference \
|
||||
--phones-dict=download/fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt
|
||||
# output/inference is not needed here, which save the static models
|
||||
rm -rf output/inference
|
||||
fi
|
@ -0,0 +1,12 @@
|
||||
#!/bin/bash
|
||||
export MAIN_ROOT=`realpath ${PWD}/../../`
|
||||
|
||||
export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
|
||||
export LC_ALL=C
|
||||
|
||||
export PYTHONDONTWRITEBYTECODE=1
|
||||
# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
|
||||
export PYTHONIOENCODING=UTF-8
|
||||
export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH}
|
||||
MODEL=fastspeech2
|
||||
export BIN_DIR=${MAIN_ROOT}/paddlespeech/t2s/exps/${MODEL}
|
@ -0,0 +1,38 @@
|
||||
#!/bin/bash
|
||||
source path.sh
|
||||
|
||||
gpus=0
|
||||
stage=0
|
||||
stop_stage=100
|
||||
|
||||
# with the following command, you can choice the stage range you want to run
|
||||
# such as `./run.sh --stage 0 --stop-stage 0`
|
||||
# this can not be mixed use with `$1`, `$2` ...
|
||||
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1
|
||||
|
||||
mkdir download
|
||||
|
||||
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
||||
# download pretrained tts models and unzip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip
|
||||
unzip -d download download/pwg_baker_ckpt_0.4.zip
|
||||
wget -P download https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
unzip -d download download/fastspeech2_nosil_baker_ckpt_0.4.zip
|
||||
fi
|
||||
|
||||
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
|
||||
# run tts
|
||||
CUDA_VISIBLE_DEVICES=${gpus} \
|
||||
python3 style_syn.py \
|
||||
--fastspeech2-config=download/fastspeech2_nosil_baker_ckpt_0.4/default.yaml \
|
||||
--fastspeech2-checkpoint=download/fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \
|
||||
--fastspeech2-stat=download/fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \
|
||||
--fastspeech2-pitch-stat=download/fastspeech2_nosil_baker_ckpt_0.4/pitch_stats.npy \
|
||||
--fastspeech2-energy-stat=download/fastspeech2_nosil_baker_ckpt_0.4/energy_stats.npy \
|
||||
--pwg-config=download/pwg_baker_ckpt_0.4/pwg_default.yaml \
|
||||
--pwg-checkpoint=download/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \
|
||||
--pwg-stat=download/pwg_baker_ckpt_0.4/pwg_stats.npy \
|
||||
--text=${BIN_DIR}/../sentences.txt \
|
||||
--output-dir=output \
|
||||
--phones-dict=download/fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt
|
||||
fi
|
@ -0,0 +1 @@
|
||||
000 谁知青蛙一落地,竟变成了一位英俊的王子。于是遵照国王的意思,他做了公主的亲密伴侣。
|
@ -0,0 +1,284 @@
|
||||
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import argparse
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import paddle
|
||||
import soundfile as sf
|
||||
import yaml
|
||||
from yacs.config import CfgNode
|
||||
|
||||
from paddlespeech.t2s.frontend.zh_frontend import Frontend
|
||||
from paddlespeech.t2s.models.fastspeech2 import FastSpeech2
|
||||
from paddlespeech.t2s.models.fastspeech2 import FastSpeech2Inference
|
||||
from paddlespeech.t2s.models.parallel_wavegan import PWGGenerator
|
||||
from paddlespeech.t2s.models.parallel_wavegan import PWGInference
|
||||
from paddlespeech.t2s.modules.normalizer import ZScore
|
||||
|
||||
|
||||
class StyleFastSpeech2Inference(FastSpeech2Inference):
|
||||
def __init__(self, normalizer, model, pitch_stats_path, energy_stats_path):
|
||||
super().__init__(normalizer, model)
|
||||
self.pitch_mean, self.pitch_std = np.load(pitch_stats_path)
|
||||
self.pitch_mean = paddle.to_tensor(self.pitch_mean)
|
||||
self.pitch_std = paddle.to_tensor(self.pitch_std)
|
||||
self.energy_mean, self.energy_std = np.load(energy_stats_path)
|
||||
self.energy_mean = paddle.to_tensor(self.energy_mean)
|
||||
self.energy_std = paddle.to_tensor(self.energy_std)
|
||||
|
||||
def denorm(self, data, mean, std):
|
||||
return data * std + mean
|
||||
|
||||
def norm(self, data, mean, std):
|
||||
return (data - mean) / std
|
||||
|
||||
def forward(self,
|
||||
text,
|
||||
durations=None,
|
||||
pitch=None,
|
||||
energy=None,
|
||||
robot=False):
|
||||
"""
|
||||
Parameters
|
||||
----------
|
||||
text : Tensor(int64)
|
||||
Input sequence of characters (T,).
|
||||
speech : Tensor, optional
|
||||
Feature sequence to extract style (N, idim).
|
||||
durations : Tensor, optional (int64)
|
||||
Groundtruth of duration (T,) or
|
||||
float/int (represents ratio)
|
||||
pitch : Tensor, optional
|
||||
Groundtruth of token-averaged pitch (T, 1) or
|
||||
float/int (represents ratio)
|
||||
energy : Tensor, optional
|
||||
Groundtruth of token-averaged energy (T, 1) or
|
||||
float (represents ratio)
|
||||
robot : bool, optional
|
||||
Weather output robot style
|
||||
Returns
|
||||
----------
|
||||
Tensor
|
||||
Output sequence of features (L, odim).
|
||||
"""
|
||||
normalized_mel, d_outs, p_outs, e_outs = self.acoustic_model.inference(
|
||||
text, durations=None, pitch=None, energy=None)
|
||||
|
||||
# set duration
|
||||
if isinstance(durations, float):
|
||||
durations = durations * d_outs
|
||||
elif isinstance(durations, paddle.Tensor):
|
||||
durations = durations
|
||||
|
||||
if robot:
|
||||
# set normed pitch to zeros have the same effect with set denormd ones to mean
|
||||
pitch = paddle.zeros(p_outs.shape)
|
||||
|
||||
# set pitch, can overwrite robot set
|
||||
if isinstance(pitch, (int, float)):
|
||||
p_Hz = paddle.exp(
|
||||
self.denorm(p_outs, self.pitch_mean, self.pitch_std))
|
||||
p_HZ = pitch * p_Hz
|
||||
pitch = self.norm(paddle.log(p_HZ), self.pitch_mean, self.pitch_std)
|
||||
elif isinstance(pitch, paddle.Tensor):
|
||||
pitch = pitch
|
||||
|
||||
# set energy
|
||||
if isinstance(energy, (int, float)):
|
||||
e_dnorm = self.denorm(e_outs, self.energy_mean, self.energy_std)
|
||||
e_dnorm = energy * e_dnorm
|
||||
energy = self.norm(e_dnorm, self.energy_mean, self.energy_std)
|
||||
elif isinstance(energy, paddle.Tensor):
|
||||
energy = energy
|
||||
|
||||
normalized_mel, d_outs, p_outs, e_outs = self.acoustic_model.inference(
|
||||
text,
|
||||
durations=durations,
|
||||
pitch=pitch,
|
||||
energy=energy,
|
||||
use_teacher_forcing=True)
|
||||
|
||||
logmel = self.normalizer.inverse(normalized_mel)
|
||||
return logmel
|
||||
|
||||
|
||||
def evaluate(args, fastspeech2_config, pwg_config):
|
||||
|
||||
# construct dataset for evaluation
|
||||
sentences = []
|
||||
with open(args.text, 'rt') as f:
|
||||
for line in f:
|
||||
utt_id, sentence = line.strip().split()
|
||||
sentences.append((utt_id, sentence))
|
||||
|
||||
with open(args.phones_dict, "r") as f:
|
||||
phn_id = [line.strip().split() for line in f.readlines()]
|
||||
vocab_size = len(phn_id)
|
||||
print("vocab_size:", vocab_size)
|
||||
|
||||
odim = fastspeech2_config.n_mels
|
||||
model = FastSpeech2(
|
||||
idim=vocab_size, odim=odim, **fastspeech2_config["model"])
|
||||
|
||||
model.set_state_dict(
|
||||
paddle.load(args.fastspeech2_checkpoint)["main_params"])
|
||||
model.eval()
|
||||
|
||||
vocoder = PWGGenerator(**pwg_config["generator_params"])
|
||||
vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"])
|
||||
vocoder.remove_weight_norm()
|
||||
vocoder.eval()
|
||||
print("model done!")
|
||||
|
||||
frontend = Frontend(phone_vocab_path=args.phones_dict)
|
||||
print("frontend done!")
|
||||
|
||||
stat = np.load(args.fastspeech2_stat)
|
||||
mu, std = stat
|
||||
mu = paddle.to_tensor(mu)
|
||||
std = paddle.to_tensor(std)
|
||||
fastspeech2_normalizer = ZScore(mu, std)
|
||||
|
||||
stat = np.load(args.pwg_stat)
|
||||
mu, std = stat
|
||||
mu = paddle.to_tensor(mu)
|
||||
std = paddle.to_tensor(std)
|
||||
pwg_normalizer = ZScore(mu, std)
|
||||
|
||||
fastspeech2_inference = StyleFastSpeech2Inference(
|
||||
fastspeech2_normalizer, model, args.fastspeech2_pitch_stat,
|
||||
args.fastspeech2_energy_stat)
|
||||
fastspeech2_inference.eval()
|
||||
|
||||
pwg_inference = PWGInference(pwg_normalizer, vocoder)
|
||||
pwg_inference.eval()
|
||||
|
||||
output_dir = Path(args.output_dir)
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
styles = ["normal", "robot", "1.2xspeed", "0.8xspeed", "child_voice"]
|
||||
for style in styles:
|
||||
robot = False
|
||||
durations = None
|
||||
pitch = None
|
||||
energy = None
|
||||
|
||||
if style == "robot":
|
||||
# all tones in phones be `1`
|
||||
# all pitch should be the same, we use mean here
|
||||
robot = True
|
||||
if style == "1.2xspeed":
|
||||
durations = 1 / 1.2
|
||||
if style == "0.8xspeed":
|
||||
durations = 1 / 0.8
|
||||
if style == "child_voice":
|
||||
pitch = 1.3
|
||||
sub_output_dir = output_dir / style
|
||||
sub_output_dir.mkdir(parents=True, exist_ok=True)
|
||||
for utt_id, sentence in sentences:
|
||||
input_ids = frontend.get_input_ids(
|
||||
sentence, merge_sentences=True, robot=robot)
|
||||
phone_ids = input_ids["phone_ids"][0]
|
||||
|
||||
with paddle.no_grad():
|
||||
mel = fastspeech2_inference(
|
||||
phone_ids,
|
||||
durations=durations,
|
||||
pitch=pitch,
|
||||
energy=energy,
|
||||
robot=robot)
|
||||
wav = pwg_inference(mel)
|
||||
|
||||
sf.write(
|
||||
str(sub_output_dir / (utt_id + ".wav")),
|
||||
wav.numpy(),
|
||||
samplerate=fastspeech2_config.fs)
|
||||
print(f"{style}_{utt_id} done!")
|
||||
|
||||
|
||||
def main():
|
||||
# parse args and config and redirect to train_sp
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Synthesize with fastspeech2 & parallel wavegan.")
|
||||
parser.add_argument(
|
||||
"--fastspeech2-config", type=str, help="fastspeech2 config file.")
|
||||
parser.add_argument(
|
||||
"--fastspeech2-checkpoint",
|
||||
type=str,
|
||||
help="fastspeech2 checkpoint to load.")
|
||||
parser.add_argument(
|
||||
"--fastspeech2-stat",
|
||||
type=str,
|
||||
help="mean and standard deviation used to normalize spectrogram when training fastspeech2."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--fastspeech2-pitch-stat",
|
||||
type=str,
|
||||
help="mean and standard deviation used to normalize pitch when training fastspeech2"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--fastspeech2-energy-stat",
|
||||
type=str,
|
||||
help="mean and standard deviation used to normalize energy when training fastspeech2."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--pwg-config", type=str, help="parallel wavegan config file.")
|
||||
parser.add_argument(
|
||||
"--pwg-checkpoint",
|
||||
type=str,
|
||||
help="parallel wavegan generator parameters to load.")
|
||||
parser.add_argument(
|
||||
"--pwg-stat",
|
||||
type=str,
|
||||
help="mean and standard deviation used to normalize spectrogram when training parallel wavegan."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--phones-dict",
|
||||
type=str,
|
||||
default="phone_id_map.txt",
|
||||
help="phone vocabulary file.")
|
||||
parser.add_argument(
|
||||
"--text",
|
||||
type=str,
|
||||
help="text to synthesize, a 'utt_id sentence' pair per line.")
|
||||
parser.add_argument("--output-dir", type=str, help="output dir.")
|
||||
parser.add_argument(
|
||||
"--ngpu", type=int, default=1, help="if ngpu == 0, use cpu.")
|
||||
parser.add_argument("--verbose", type=int, default=1, help="verbose.")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if args.ngpu == 0:
|
||||
paddle.set_device("cpu")
|
||||
elif args.ngpu > 0:
|
||||
paddle.set_device("gpu")
|
||||
else:
|
||||
print("ngpu should >= 0 !")
|
||||
|
||||
with open(args.fastspeech2_config) as f:
|
||||
fastspeech2_config = CfgNode(yaml.safe_load(f))
|
||||
with open(args.pwg_config) as f:
|
||||
pwg_config = CfgNode(yaml.safe_load(f))
|
||||
|
||||
print("========Args========")
|
||||
print(yaml.safe_dump(vars(args)))
|
||||
print("========Config========")
|
||||
print(fastspeech2_config)
|
||||
print(pwg_config)
|
||||
|
||||
evaluate(args, fastspeech2_config, pwg_config)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
After Width: | Height: | Size: 47 KiB |
After Width: | Height: | Size: 117 KiB |
After Width: | Height: | Size: 108 KiB |
After Width: | Height: | Size: 224 KiB |
After Width: | Height: | Size: 1.5 MiB |
After Width: | Height: | Size: 581 KiB |
After Width: | Height: | Size: 368 KiB |