import os os.system('cd monotonic_align && python setup.py build_ext --inplace && cd ..') os.system('pip install pypinyin Cython==0.29.21 librosa==0.8.0 matplotlib==3.3.1 numpy==1.18.5 phonemizer==2.2.1 scipy==1.5.2 Unidecode==1.1.1 >log.log') os.system('sudo apt-get install espeak -y >log.log') os.system('pip install gdown >log.log') os.system('pip install pyopenjtalk janome > log.log') os.system('pip install cloud-tpu-client > log.log') import logging numba_logger = logging.getLogger('numba') numba_logger.setLevel(logging.WARNING) import librosa import matplotlib.pyplot as plt import IPython.display as ipd import os import json import math import torch from torch import nn from torch.nn import functional as F from torch.utils.data import DataLoader import commons import utils from data_utils import TextAudioLoader, TextAudioCollate, TextAudioSpeakerLoader, TextAudioSpeakerCollate from models import SynthesizerTrn from text.symbols import symbols from text.cleaners import japanese_phrase_cleaners from text import cleaned_text_to_sequence from pypinyin import lazy_pinyin, Style from scipy.io.wavfile import write def get_text(text, hps): text_norm = cleaned_text_to_sequence(text) if hps.data.add_blank: text_norm = commons.intersperse(text_norm, 0) text_norm = torch.LongTensor(text_norm) return text_norm # hps_ms = utils.get_hparams_from_file("./configs/vctk_base.json") hps = utils.get_hparams_from_file("./configs/tokaiteio.json") # net_g_ms = SynthesizerTrn( # len(symbols), # hps_ms.data.filter_length // 2 + 1, # hps_ms.train.segment_size // hps.data.hop_length, # n_speakers=hps_ms.data.n_speakers, # **hps_ms.model) net_g = SynthesizerTrn( len(symbols), hps.data.filter_length // 2 + 1, hps.train.segment_size // hps.data.hop_length, **hps.model) _ = net_g.eval() def tts(text): if len(text) > 150: return "Error: Text is too long", None stn_tst = get_text(text, hps) with torch.no_grad(): x_tst = stn_tst.unsqueeze(0) x_tst_lengths = torch.LongTensor([stn_tst.size(0)]) audio = net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][0,0].data.float().numpy() ipd.display(ipd.Audio(audio, rate=hps.data.sampling_rate)) def tts_fn(text, speaker_id): if len(text) > 150: return "Error: Text is too long", None stn_tst = get_text(text, hps) with torch.no_grad(): x_tst = stn_tst.unsqueeze(0) x_tst_lengths = LongTensor([stn_tst.size(0)]) audio = net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][ 0, 0].data.cpu().float().numpy() return "Success", (hps.data.sampling_rate, audio) if __name__ == '__main__': _ = utils.load_checkpoint("G_50000.pth", net_g, None) app = gr.Blocks() with app: with gr.Tabs(): with gr.Column(): tts_input1 = gr.TextArea(label="Text (150 words limitation)", value="こんにちは。") tts_submit = gr.Button("Generate", variant="primary") tts_output1 = gr.Textbox(label="Output Message") tts_output2 = gr.Audio(label="Output Audio") tts_submit.click(tts_fn, [tts_input1, tts_input2], [tts_output1, tts_output2]) app.launch()