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| from models import SynthesizerTrn | |
| from vits_pinyin import VITS_PinYin | |
| from text import cleaned_text_to_sequence | |
| from text.symbols import symbols | |
| import gradio as gr | |
| import utils | |
| import torch | |
| import argparse | |
| import os | |
| import re | |
| import logging | |
| logging.getLogger('numba').setLevel(logging.WARNING) | |
| limitation = os.getenv("SYSTEM") == "spaces" | |
| def create_calback(net_g: SynthesizerTrn, tts_front: VITS_PinYin): | |
| def tts_calback(text, dur_scale): | |
| if limitation: | |
| text_len = len(re.sub("\[([A-Z]{2})\]", "", text)) | |
| max_len = 150 | |
| if text_len > max_len: | |
| return "Error: Text is too long", None | |
| phonemes, char_embeds = tts_front.chinese_to_phonemes(text) | |
| input_ids = cleaned_text_to_sequence(phonemes) | |
| with torch.no_grad(): | |
| x_tst = torch.LongTensor(input_ids).unsqueeze(0).to(device) | |
| x_tst_lengths = torch.LongTensor([len(input_ids)]).to(device) | |
| x_tst_prosody = torch.FloatTensor( | |
| char_embeds).unsqueeze(0).to(device) | |
| audio = net_g.infer(x_tst, x_tst_lengths, x_tst_prosody, noise_scale=0.5, | |
| length_scale=dur_scale)[0][0, 0].data.cpu().float().numpy() | |
| del x_tst, x_tst_lengths, x_tst_prosody | |
| return "Success", (16000, audio) | |
| return tts_calback | |
| example = [['天空呈现的透心的蓝，像极了当年。总在这样的时候，透过窗棂，心，在天空里无尽的游弋！柔柔的，浓浓的，痴痴的风，牵引起心底灵动的思潮；情愫悠悠，思情绵绵，风里默坐，红尘中的浅醉，诗词中的优柔，任那自在飞花轻似梦的情怀，裁一束霓衣，织就清浅淡薄的安寂。', 1], | |
| ['风的影子翻阅过淡蓝色的信笺，柔和的文字浅浅地漫过我安静的眸，一如几朵悠闲的云儿，忽而氤氲成汽，忽而修饰成花，铅华洗尽后的透彻和靓丽，爽爽朗朗，轻轻盈盈', 1], | |
| ['时光仿佛有穿越到了从前，在你诗情画意的眼波中，在你舒适浪漫的暇思里，我如风中的思绪徜徉广阔天际，仿佛一片沾染了快乐的羽毛，在云环影绕颤动里浸润着风的呼吸，风的诗韵，那清新的耳语，那婉约的甜蜜，那恬淡的温馨，将一腔情澜染得愈发的缠绵。', 1],] | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--share", action="store_true", | |
| default=False, help="share gradio app") | |
| args = parser.parse_args() | |
| device = torch.device("cpu") | |
| # pinyin | |
| tts_front = VITS_PinYin("./bert", device) | |
| # config | |
| hps = utils.get_hparams_from_file("./configs/bert_vits.json") | |
| # model | |
| net_g = SynthesizerTrn( | |
| len(symbols), | |
| hps.data.filter_length // 2 + 1, | |
| hps.train.segment_size // hps.data.hop_length, | |
| **hps.model) | |
| model_path = "vits_bert_model.pth" | |
| utils.load_model(model_path, net_g) | |
| net_g.eval() | |
| net_g.to(device) | |
| tts_calback = create_calback(net_g, tts_front) | |
| app = gr.Blocks() | |
| with app: | |
| gr.Markdown("# Best TTS based on BERT and VITS with some Natural Speech Features Of Microsoft\n\n" | |
| "code : github.com/PlayVoice/vits_chinese\n\n" | |
| "1, Hidden prosody embedding from BERT，get natural pauses in grammar\n\n" | |
| "2, Infer loss from NaturalSpeech，get less sound error\n\n" | |
| "3, Framework of VITS，get high audio quality\n\n" | |
| "<video id='video' controls='' preload='yes'>\n\n" | |
| "<source id='mp4' src='https://user-images.githubusercontent.com/16432329/220678182-4775dec8-9229-4578-870f-2eebc3a5d660.mp4' type='video/mp4'>\n\n" | |
| "</videos>\n\n" | |
| ) | |
| with gr.Tabs(): | |
| with gr.TabItem("TTS"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| textbox = gr.TextArea(label="Text", | |
| placeholder="Type your sentence here (Maximum 150 words)", | |
| value="中文语音合成", elem_id=f"tts-input") | |
| duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1, | |
| label='速度 Speed') | |
| with gr.Column(): | |
| text_output = gr.Textbox(label="Message") | |
| audio_output = gr.Audio( | |
| label="Output Audio", elem_id="tts-audio") | |
| btn = gr.Button("Generate!") | |
| btn.click(tts_calback, | |
| inputs=[textbox, duration_slider], | |
| outputs=[text_output, audio_output]) | |
| gr.Examples( | |
| examples=example, | |
| inputs=[textbox, duration_slider], | |
| outputs=[text_output, audio_output], | |
| fn=tts_calback | |
| ) | |
| app.queue(concurrency_count=3).launch(show_api=False, share=args.share) | |