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| import torch | |
| import numpy as np | |
| import sys | |
| import commons | |
| import utils | |
| from models import SynthesizerTrn | |
| from text.symbols import symbols | |
| from text import text_to_sequence | |
| from scipy.io.wavfile import write | |
| import logging | |
| numba_logger = logging.getLogger('numba') | |
| numba_logger.setLevel(logging.WARNING) | |
| sys.path.append("../") | |
| from resemblyzer import preprocess_wav, VoiceEncoder | |
| device = "cpu" | |
| def get_text(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 get_speaker_embedding(path): | |
| encoder = VoiceEncoder(device='cpu') | |
| wav = preprocess_wav(path) | |
| embed = encoder.embed_utterance(wav) | |
| return embed | |
| class VoiceClone(): | |
| def __init__(self, checkpoint_path): | |
| hps = utils.get_hparams_from_file("./configs/vivos.json") | |
| self.net_g = SynthesizerTrn( | |
| len(symbols), | |
| hps.data.filter_length // 2 + 1, | |
| hps.train.segment_size // hps.data.hop_length, | |
| n_speakers=hps.data.n_speakers, | |
| **hps.model).to(device) | |
| _ = self.net_g.eval() | |
| _ = utils.load_checkpoint(checkpoint_path, self.net_g, None) | |
| self.hps = hps | |
| def infer(self, text, ref_audio): | |
| stn_tst = get_text(text, self.hps) | |
| with torch.no_grad(): | |
| x_tst = stn_tst.to(device).unsqueeze(0) | |
| x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(device) | |
| speaker_embedding = get_speaker_embedding(ref_audio) | |
| speaker_embedding = torch.FloatTensor(torch.from_numpy(speaker_embedding)).unsqueeze(0).to(device) | |
| audio = self.net_g.infer(x_tst, x_tst_lengths, speaker_embedding=speaker_embedding, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][0,0].data.cpu().float().numpy() | |
| write(ref_audio.replace(".wav", "_clone.wav"), 22050, audio) | |
| if __name__ == "__main__": | |
| object = VoiceClone("logs/vivos/G_9000.pth") | |
| object.infer("hai ba hai ba", "audio/sontung.wav") |