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import romajitable |
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import re |
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import numpy as np |
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import logging |
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logging.getLogger('numba').setLevel(logging.WARNING) |
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import IPython.display as ipd |
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import torch |
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import commons |
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import utils |
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from models import SynthesizerTrn |
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from text.symbols import symbols |
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from text import text_to_sequence |
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import gradio as gr |
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import time |
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import datetime |
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import os |
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def get_text(text, hps): |
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text_norm = text_to_sequence(text, symbols, hps.data.text_cleaners) |
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if hps.data.add_blank: |
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text_norm = commons.intersperse(text_norm, 0) |
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text_norm = torch.LongTensor(text_norm) |
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return text_norm |
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dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") |
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def selection(speaker): |
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if speaker == "高咲侑": |
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spk = 0 |
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return spk |
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elif speaker == "歩夢": |
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spk = 1 |
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return spk |
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elif speaker == "かすみ": |
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spk = 2 |
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return spk |
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elif speaker == "しずく": |
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spk = 3 |
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return spk |
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elif speaker == "果林": |
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spk = 4 |
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return spk |
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elif speaker == "愛": |
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spk = 5 |
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return spk |
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elif speaker == "彼方": |
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spk = 6 |
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return spk |
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elif speaker == "せつ菜": |
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spk = 7 |
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return spk |
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elif speaker == "エマ": |
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spk = 8 |
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return spk |
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elif speaker == "璃奈": |
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spk = 9 |
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return spk |
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elif speaker == "栞子": |
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spk = 10 |
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return spk |
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elif speaker == "ランジュ": |
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spk = 11 |
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return spk |
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elif speaker == "ミア": |
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spk = 12 |
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return spk |
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elif speaker == "三色绘恋1": |
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spk = 13 |
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return spk |
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elif speaker == "三色绘恋2": |
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spk = 15 |
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elif speaker == "派蒙": |
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spk = 16 |
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return spk |
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def is_japanese(string): |
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for ch in string: |
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if ord(ch) > 0x3040 and ord(ch) < 0x30FF: |
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return True |
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return False |
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def is_english(string): |
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import re |
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pattern = re.compile('^[A-Za-z0-9.,:;!?()_*"\' ]+$') |
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if pattern.fullmatch(string): |
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return True |
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else: |
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return False |
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def sle(language,tts_input0): |
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if language == "中文": |
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tts_input1 = "[ZH]" + tts_input0.replace('\n','。').replace(' ',',') + "[ZH]" |
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return tts_input1 |
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if language == "自动": |
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tts_input1 = f"[JA]{tts_input0}[JA]" if is_japanese(tts_input0) else f"[ZH]{tts_input0}[ZH]" |
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return tts_input1 |
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elif language == "日文": |
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tts_input1 = "[JA]" + tts_input0.replace('\n','。').replace(' ',',') + "[JA]" |
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return tts_input1 |
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def extrac(text): |
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text = re.sub("<[^>]*>","",text) |
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result_list = re.split(r'\n', text) |
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final_list = [] |
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for i in result_list: |
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if is_english(i): |
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i = romajitable.to_kana(i).katakana |
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i = i.replace('\n','').replace(' ','') |
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if len(i)>1: |
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if len(i) > 20: |
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try: |
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cur_list = re.split(r'。|!', i) |
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for i in cur_list: |
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if len(i)>1: |
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final_list.append(i+'。') |
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except: |
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pass |
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else: |
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final_list.append(i) |
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final_list = [x for x in final_list if x != ''] |
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print(final_list) |
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return final_list |
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def infer(text ,language, speaker_id,n_scale= 0.667,n_scale_w = 0.8, l_scale = 1): |
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speaker_id = int(selection(speaker_id)) |
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a = ['【','[','(','('] |
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b = ['】',']',')',')'] |
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for i in a: |
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text = text.replace(i,'<') |
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for i in b: |
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text = text.replace(i,'>') |
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final_list = extrac(text.replace('“','').replace('”','')) |
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audio_fin = [] |
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c = 0 |
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t = datetime.timedelta(seconds=0) |
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f1 = open("subtitles.srt",'w',encoding='utf-8') |
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for sentence in final_list: |
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c +=1 |
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stn_tst = get_text(sle(language,sentence), hps_ms) |
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with torch.no_grad(): |
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x_tst = stn_tst.unsqueeze(0).to(dev) |
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x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(dev) |
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sid = torch.LongTensor([speaker_id]).to(dev) |
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t1 = time.time() |
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audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=n_scale, noise_scale_w=n_scale_w, length_scale=l_scale)[0][0,0].data.cpu().float().numpy() |
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t2 = time.time() |
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spending_time = "第"+str(c)+"句的推理时间为:"+str(t2-t1)+"s" |
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print(spending_time) |
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time_start = str(t).split(".")[0] + "," + str(t.microseconds)[:3] |
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last_time = datetime.timedelta(seconds=len(audio)/float(22050)) |
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t+=last_time |
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time_end = str(t).split(".")[0] + "," + str(t.microseconds)[:3] |
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print(time_end) |
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f1.write(str(c-1)+'\n'+time_start+' --> '+time_end+'\n'+sentence+'\n\n') |
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audio_fin.append(audio) |
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file_path = "subtitles.srt" |
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return (hps_ms.data.sampling_rate, np.concatenate(audio_fin)),file_path |
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lan = ["中文","日文","自动"] |
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idols = ["高咲侑","歩夢","かすみ","しずく","果林","愛","せつ菜","璃奈","栞子","エマ","ランジュ","ミア","派蒙"] |
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hps_ms = utils.get_hparams_from_file("lovelive/config.json") |
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net_g_ms = SynthesizerTrn( |
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len(symbols), |
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hps_ms.data.filter_length // 2 + 1, |
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hps_ms.train.segment_size // hps_ms.data.hop_length, |
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n_speakers=hps_ms.data.n_speakers, |
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**hps_ms.model).to(dev) |
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_ = net_g_ms.eval() |
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_ = utils.load_checkpoint("lovelive/G_936000.pth", net_g_ms) |
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inputs = [gr.TextArea(label="如需实现快速合成,建议在colab上克隆后运行本仓库", value="为什么你会那么熟练啊?你和雪菜亲过多少次了?我想做只属于你一个人的学院偶像,所以,请只注视我一个人,好吗?【中文】\nなんでそんなに慣れてんだよっ?せつ菜と…何回キスしたんだよ?どこまであたしを置いてきぼりにすれば気が済むんだよ?[日文]\nI can't choose just one(English)"), |
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gr.Dropdown(label="选择语言,目前勉强可以做到自动识别",choices=lan, value="自动", interactive=True), |
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gr.Dropdown(label="选择说话人",choices=idols, value="歩夢", interactive=True), |
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gr.Slider(minimum= 0,maximum=1.0,label="更改噪声比例,以控制情感", value=0.267), |
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gr.Slider(minimum= 0,maximum=1.0,label="更改噪声偏差,以控制音素长短", value=0.7), |
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gr.Slider(minimum= 0.1,maximum=10,label="更改时间比例", value=1)] |
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outputs=[gr.Audio(label="采样率22050"), gr.outputs.File(label="字幕文件:subtitles.srt")] |
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iface = gr.Interface( |
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fn=infer, |
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inputs=inputs, |
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outputs=outputs, |
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title="Vits", |
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description="虹团11人模型", |
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) |
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iface.launch() |