mirror of
https://github.com/BoardWare-Genius/jarvis-models.git
synced 2025-12-13 16:53:24 +00:00
60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
import io
|
||
import sys
|
||
import time
|
||
|
||
sys.path.append('tts/vits')
|
||
|
||
import numpy as np
|
||
import soundfile
|
||
import os
|
||
os.environ["PYTORCH_JIT"] = "0"
|
||
import torch
|
||
|
||
import tts.vits.commons as commons
|
||
import tts.vits.utils as utils
|
||
|
||
from tts.vits.models import SynthesizerTrn
|
||
from tts.vits.text.symbols import symbols
|
||
from tts.vits.text import text_to_sequence
|
||
|
||
import logging
|
||
logging.getLogger().setLevel(logging.INFO)
|
||
logging.basicConfig(level=logging.INFO)
|
||
|
||
|
||
class TTService():
|
||
|
||
def __init__(self, cfg, model, char, speed):
|
||
logging.info('Initializing TTS Service for %s...' % char)
|
||
self.hps = utils.get_hparams_from_file(cfg)
|
||
self.speed = speed
|
||
self.net_g = SynthesizerTrn(
|
||
len(symbols),
|
||
self.hps.data.filter_length // 2 + 1,
|
||
self.hps.train.segment_size // self.hps.data.hop_length,
|
||
**self.hps.model).cpu()
|
||
_ = self.net_g.eval()
|
||
_ = utils.load_checkpoint(model, self.net_g, None)
|
||
|
||
def get_text(self, text, hps):
|
||
text_norm = text_to_sequence(text, hps.data.text_cleaners)
|
||
if hps.data.add_blank:
|
||
text_norm = commons.intersperse(text_norm, 0)
|
||
text_norm = torch.LongTensor(text_norm)
|
||
return text_norm
|
||
|
||
def read(self, text, format="wav") -> io.BytesIO:
|
||
text = text.replace('~', '！')
|
||
stn_tst = self.get_text(text, self.hps)
|
||
|
||
with torch.no_grad():
|
||
x_tst = stn_tst.cpu().unsqueeze(0)
|
||
x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).cpu()
|
||
# tp = self.net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.2, length_scale=self.speed)
|
||
audio = self.net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.2, length_scale=self.speed)[0][
|
||
0, 0].data.cpu().float().numpy()
|
||
f = io.BytesIO()
|
||
soundfile.write(f, audio, self.hps.data.sampling_rate, format=format)
|
||
f.seek(0)
|
||
return f
|
||
|