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| import gradio as gr | |
| import torch | |
| import commons | |
| import utils | |
| from models import SynthesizerTrn | |
| from text.symbols import symbols | |
| from text import text_to_sequence | |
| import numpy as np | |
| import os | |
| import translators.server as tss | |
| 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 | |
| hps = utils.get_hparams_from_file("./configs/uma87.json") | |
| 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) | |
| _ = net_g.eval() | |
| _ = utils.load_checkpoint("pretrained_models/G_1153000.pth", net_g, None) | |
| title = "Umamusume voice synthesizer \n 赛马娘语音合成器" | |
| description = """ | |
| This synthesizer is created based on VITS (https://arxiv.org/abs/2106.06103) model, trained on voice data extracted from mobile game Umamusume Pretty Derby\n | |
| 这个合成器是基于VITS文本到语音模型，在从手游《賽馬娘：Pretty Derby》解包的语音数据上训练得到。\n | |
| If your input language is not Japanese, it will be translated to Japanese by Google translator, but accuracy is not guaranteed.\n | |
| 如果您的输入语言不是日语，则会由谷歌翻译自动翻译为日语，但是准确性不能保证。\n\n | |
| 若使用人数太多可能会出现排队过久的情况，若有需要可选择本地部署\n\n | |
| """ | |
| article = """ | |
| """ | |
| def infer(text, character, language, duration, noise_scale, noise_scale_w): | |
| if language == '日本語': | |
| pass | |
| elif language == '简体中文': | |
| text = tss.google(text, from_language='zh', to_language='ja') | |
| elif language == 'English': | |
| text = tss.google(text, from_language='en', to_language='ja') | |
| char_id = int(character.split(':')[0]) | |
| 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)]) | |
| sid = torch.LongTensor([char_id]) | |
| audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=duration)[0][0,0].data.cpu().float().numpy() | |
| return (text,(22050, audio)) | |
| # We instantiate the Textbox class | |
| textbox = gr.Textbox(label="Text", placeholder="Type your sentence here", lines=2) | |
| # select character | |
| char_dropdown = gr.Dropdown(['0:特别周','1:无声铃鹿','2:东海帝王','3:丸善斯基', | |
| '4:富士奇迹','5:小栗帽','6:黄金船','7:伏特加', | |
| '8:大和赤骥','9:大树快车','10:草上飞','11:菱亚马逊', | |
| '12:目白麦昆','13:神鹰','14:好歌剧','15:成田白仁', | |
| '16:鲁道夫象征','17:气槽','18:爱丽数码','19:青云天空', | |
| '20:玉藻十字','21:美妙姿势','22:琵琶晨光','23:重炮', | |
| '24:曼城茶座','25:美普波旁','26:目白雷恩','27:菱曙', | |
| '28:雪之美人','29:米浴','30:艾尼斯风神','31:爱丽速子', | |
| '32:爱慕织姬','33:稻荷一','34:胜利奖券','35:空中神宫', | |
| '36:荣进闪耀','37:真机伶','38:川上公主','39:黄金城市', | |
| '40:樱花进王','41:采珠','42:新光风','43:东商变革', | |
| '44:超级小溪','45:醒目飞鹰','46:荒漠英雄','47:东瀛佐敦', | |
| '48:中山庆典','49:成田大进','50:西野花','51:春乌拉拉', | |
| '52:青竹回忆','53:微光飞驹','54:美丽周日','55:待兼福来', | |
| '56:Mr.C.B','57:名将怒涛','58:目白多伯','59:优秀素质', | |
| '60:帝王光环','61:待兼诗歌剧','62:生野狄杜斯','63:目白善信', | |
| '64:大拓太阳神','65:双涡轮','66:里见光钻','67:北部玄驹', | |
| '68:樱花千代王','69:天狼星象征','70:目白阿尔丹','71:八重无敌', | |
| '72:鹤丸刚志','73:目白光明','74:樱花桂冠','75:成田路', | |
| '76:也文摄辉','77:吉兆','78:谷野美酒','79:第一红宝石', | |
| '80:真弓快车','81:骏川手纲','82:凯斯奇迹','83:小林历奇', | |
| '84:北港火山','85:奇锐骏','86:秋川理事长']) | |
| language_dropdown = gr.Dropdown(['日本語','简体中文','English', 1, 0.667, 0.8]) | |
| examples = [['お疲れ様です，トレーナーさん。', '1:无声铃鹿', '日本語', 1, 0.667, 0.8], | |
| ['張り切っていこう！', '67:北部玄驹', '日本語', 1, 0.667, 0.8], | |
| ['何でこんなに慣れでんのよ，私のほが先に好きだっだのに。', '10:草上飞','日本語', 1, 0.667, 0.8], | |
| ['授業中に出しだら，学校生活終わるですわ。', '12:目白麦昆','日本語', 1, 0.667, 0.8], | |
| ['お帰りなさい，お兄様！', '29:米浴','日本語', 1, 0.667, 0.8], | |
| ['私の処女をもらっでください！', '29:米浴','日本語', 1, 0.667, 0.8]] | |
| duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1, label='时长 Duration') | |
| noise_scale_slider = gr.Slider(minimum=0.1, maximum=5, value=0.667, step=0.001, label='噪声比例 noise_scale') | |
| noise_scale_w_slider = gr.Slider(minimum=0.1, maximum=5, value=0.8, step=0.1, label='噪声偏差 noise_scale_w') | |
| gr.Interface(fn=infer, inputs=[textbox, char_dropdown, language_dropdown, duration_slider, noise_scale_slider, noise_scale_w_slider,], outputs=["text","audio"],title=title, description=description, article=article, examples=examples).launch() |