You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
198 lines
6.3 KiB
198 lines
6.3 KiB
# Copyright (c) 2022 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 paddle
|
|
import soundfile as sf
|
|
import yaml
|
|
from timer import timer
|
|
from yacs.config import CfgNode
|
|
|
|
from paddlespeech.t2s.exps.syn_utils import am_to_static
|
|
from paddlespeech.t2s.exps.syn_utils import get_frontend
|
|
from paddlespeech.t2s.exps.syn_utils import get_sentences
|
|
from paddlespeech.t2s.models.vits import VITS
|
|
from paddlespeech.t2s.models.vits import VITSInference
|
|
from paddlespeech.t2s.utils import str2bool
|
|
|
|
|
|
def evaluate(args):
|
|
# Init body.
|
|
with open(args.config) as f:
|
|
config = CfgNode(yaml.safe_load(f))
|
|
|
|
print("========Args========")
|
|
print(yaml.safe_dump(vars(args)))
|
|
print("========Config========")
|
|
print(config)
|
|
|
|
sentences = get_sentences(text_file=args.text, lang=args.lang)
|
|
|
|
# frontend
|
|
frontend = get_frontend(lang=args.lang, phones_dict=args.phones_dict)
|
|
# acoustic model
|
|
am_name = args.am[:args.am.rindex('_')]
|
|
am_dataset = args.am[args.am.rindex('_') + 1:]
|
|
|
|
spk_num = None
|
|
if args.speaker_dict is not None:
|
|
print("multiple speaker vits!")
|
|
with open(args.speaker_dict, 'rt') as f:
|
|
spk_id = [line.strip().split() for line in f.readlines()]
|
|
spk_num = len(spk_id)
|
|
else:
|
|
print("single speaker vits!")
|
|
print("spk_num:", spk_num)
|
|
|
|
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 = config.n_fft // 2 + 1
|
|
config["model"]["generator_params"]["spks"] = spk_num
|
|
|
|
vits = VITS(idim=vocab_size, odim=odim, **config["model"])
|
|
vits.set_state_dict(paddle.load(args.ckpt)["main_params"])
|
|
vits.eval()
|
|
|
|
vits_inference = VITSInference(vits)
|
|
# whether dygraph to static
|
|
if args.inference_dir:
|
|
vits_inference = am_to_static(
|
|
am_inference=vits_inference,
|
|
am=args.am,
|
|
inference_dir=args.inference_dir,
|
|
speaker_dict=args.speaker_dict)
|
|
|
|
output_dir = Path(args.output_dir)
|
|
output_dir.mkdir(parents=True, exist_ok=True)
|
|
merge_sentences = False
|
|
add_blank = args.add_blank
|
|
|
|
N = 0
|
|
T = 0
|
|
for utt_id, sentence in sentences:
|
|
with timer() as t:
|
|
if args.lang == 'zh':
|
|
input_ids = frontend.get_input_ids(
|
|
sentence,
|
|
merge_sentences=merge_sentences,
|
|
add_blank=add_blank)
|
|
phone_ids = input_ids["phone_ids"]
|
|
elif args.lang == 'en':
|
|
input_ids = frontend.get_input_ids(
|
|
sentence, merge_sentences=merge_sentences)
|
|
phone_ids = input_ids["phone_ids"]
|
|
else:
|
|
print("lang should in {'zh', 'en'}!")
|
|
with paddle.no_grad():
|
|
flags = 0
|
|
for i in range(len(phone_ids)):
|
|
part_phone_ids = phone_ids[i]
|
|
spk_id = None
|
|
if am_dataset in {"aishell3",
|
|
"vctk"} and spk_num is not None:
|
|
spk_id = paddle.to_tensor(args.spk_id)
|
|
wav = vits_inference(part_phone_ids, spk_id)
|
|
else:
|
|
wav = vits_inference(part_phone_ids)
|
|
if flags == 0:
|
|
wav_all = wav
|
|
flags = 1
|
|
else:
|
|
wav_all = paddle.concat([wav_all, wav])
|
|
wav = wav_all.numpy()
|
|
N += wav.size
|
|
T += t.elapse
|
|
speed = wav.size / t.elapse
|
|
rtf = config.fs / speed
|
|
print(
|
|
f"{utt_id}, wave: {wav.shape}, time: {t.elapse}s, Hz: {speed}, RTF: {rtf}."
|
|
)
|
|
sf.write(str(output_dir / (utt_id + ".wav")), wav, samplerate=config.fs)
|
|
print(f"{utt_id} done!")
|
|
print(f"generation speed: {N / T}Hz, RTF: {config.fs / (N / T) }")
|
|
|
|
|
|
def parse_args():
|
|
# parse args and config
|
|
parser = argparse.ArgumentParser(description="Synthesize with VITS")
|
|
|
|
# model
|
|
parser.add_argument(
|
|
'--config', type=str, default=None, help='Config of VITS.')
|
|
parser.add_argument(
|
|
'--ckpt', type=str, default=None, help='Checkpoint file of VITS.')
|
|
parser.add_argument(
|
|
"--phones_dict", type=str, default=None, help="phone vocabulary file.")
|
|
parser.add_argument(
|
|
"--speaker_dict", type=str, default=None, help="speaker id map file.")
|
|
parser.add_argument(
|
|
'--spk_id',
|
|
type=int,
|
|
default=0,
|
|
help='spk id for multi speaker acoustic model')
|
|
# other
|
|
parser.add_argument(
|
|
'--lang',
|
|
type=str,
|
|
default='zh',
|
|
help='Choose model language. zh or en')
|
|
|
|
parser.add_argument(
|
|
"--inference_dir",
|
|
type=str,
|
|
default=None,
|
|
help="dir to save inference models")
|
|
parser.add_argument(
|
|
"--ngpu", type=int, default=1, help="if ngpu == 0, use cpu.")
|
|
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(
|
|
"--add-blank",
|
|
type=str2bool,
|
|
default=True,
|
|
help="whether to add blank between phones")
|
|
parser.add_argument(
|
|
'--am',
|
|
type=str,
|
|
default='vits_csmsc',
|
|
help='Choose acoustic model type of tts task.')
|
|
|
|
args = parser.parse_args()
|
|
return args
|
|
|
|
|
|
def main():
|
|
args = parse_args()
|
|
|
|
if args.ngpu == 0:
|
|
paddle.set_device("cpu")
|
|
elif args.ngpu > 0:
|
|
paddle.set_device("gpu")
|
|
else:
|
|
print("ngpu should >= 0 !")
|
|
|
|
evaluate(args)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|