import torch import librosa import commons import utils from models import SynthesizerTrn from text import text_to_sequence import numpy as np from mel_processing import spectrogram_torch import gradio as gr from text.cleaners import shanghainese_cleaners DEFAULT_TEXT='阿拉小人天天辣辣白相,书一眼也勿看,拿我急煞脱了。侬讲是𠲎?' def clean_text(text,ipa_input): if ipa_input: return shanghainese_cleaners(text) return text def get_text(text, hps, cleaned=False): if cleaned: text_norm = text_to_sequence(text, hps.symbols, []) else: text_norm = text_to_sequence(text, hps.symbols, 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 speech_synthesize(text, cleaned, length_scale): text=text.replace('\n','') print(text) stn_tst = get_text(text, hps_ms, cleaned) with torch.no_grad(): x_tst = stn_tst.unsqueeze(0) x_tst_lengths = torch.LongTensor([stn_tst.size(0)]) sid = torch.LongTensor([0]) audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=0.667, noise_scale_w=0.8, length_scale=length_scale)[0][0,0].data.cpu().float().numpy() return (hps_ms.data.sampling_rate, audio) if __name__=='__main__': hps_ms = utils.get_hparams_from_file('model/config.json') n_speakers = hps_ms.data.n_speakers n_symbols = len(hps_ms.symbols) speakers = hps_ms.speakers net_g_ms = SynthesizerTrn( n_symbols, hps_ms.data.filter_length // 2 + 1, hps_ms.train.segment_size // hps_ms.data.hop_length, n_speakers=n_speakers, **hps_ms.model) _ = net_g_ms.eval() utils.load_checkpoint('model/model.pth', net_g_ms) with gr.Blocks() as app: gr.Markdown('# Shanghainese Text to Speech\n' '![visitor badge](https://visitor-badge.glitch.me/badge?page_id=cjangcjengh.shanghainese-tts)') gr.Markdown('
See EXAMPLES on Shanghainese script
') text_input = gr.TextArea(label='Text', placeholder='Type your text here',value=DEFAULT_TEXT) cleaned_text=gr.Checkbox(label='IPA Input',default=True) length_scale=gr.Slider(0.5,2,1,step=0.1,label='Speaking Speed',interactive=True) tts_button = gr.Button('Synthesize') audio_output = gr.Audio(label='Speech Synthesized') cleaned_text.change(clean_text,[text_input,cleaned_text],[text_input]) tts_button.click(speech_synthesize,[text_input,cleaned_text,length_scale],[audio_output]) gr.Markdown('## Based on\n' '- [https://github.com/jaywalnut310/vits](https://github.com/jaywalnut310/vits)\n\n' '## Dataset\n' '- [http://shh.dict.cn/](http://shh.dict.cn/)\n\n' '## Lexicon\n' '- [https://www.wugniu.com/](https://www.wugniu.com/)\n\n' '- [https://github.com/MaigoAkisame/MCPDict](https://github.com/MaigoAkisame/MCPDict)\n\n' '- [https://github.com/edward-martyr/rime-yahwe_zaonhe](https://github.com/edward-martyr/rime-yahwe_zaonhe)') app.launch()