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import torch | |
import scipy.io.wavfile | |
from espnet2.bin.tts_inference import Text2Speech | |
from espnet2.utils.types import str_or_none | |
tagen = 'kan-bayashi/ljspeech_vits' | |
vocoder_tagen = "none" | |
text2speechen = Text2Speech.from_pretrained( | |
model_tag=str_or_none(tagen), | |
vocoder_tag=str_or_none(vocoder_tagen), | |
device="cpu", | |
# Only for Tacotron 2 & Transformer | |
threshold=0.5, | |
# Only for Tacotron 2 | |
minlenratio=0.0, | |
maxlenratio=10.0, | |
use_att_constraint=False, | |
backward_window=1, | |
forward_window=3, | |
# Only for FastSpeech & FastSpeech2 & VITS | |
speed_control_alpha=1.0, | |
# Only for VITS | |
noise_scale=0.333, | |
noise_scale_dur=0.333, | |
) | |
def inference(text, lang): | |
print("Converting to Audio") | |
with torch.no_grad(): | |
if lang == "english": | |
wav = text2speechen(text)["wav"] | |
scipy.io.wavfile.write( | |
"./audio/out.wav", text2speechen.fs, wav.view(-1).cpu().numpy()) | |
return "./audio/out.wav" | |