mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-10-06 22:50:00 +08:00
Use TTSFRD process text
This commit is contained in:
KamioRinn
parent
8d91183c4c
commit
efe803f589
@ -252,13 +252,13 @@ def clean_text_inf(text, language):
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dtype=torch.float16 if is_half == True else torch.float32
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def get_bert_inf(phones, word2ph, norm_text, language):
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language=language.replace("all_","")
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if language == "zh":
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bert = get_bert_feature(norm_text, word2ph).to(device)#.to(dtype)
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else:
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bert = torch.zeros(
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(1024, len(phones)),
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dtype=torch.float16 if is_half == True else torch.float32,
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).to(device)
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# if language == "zh":
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# bert = get_bert_feature(norm_text, word2ph).to(device)#.to(dtype)
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# else:
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bert = torch.zeros(
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(1024, len(phones)),
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dtype=torch.float16 if is_half == True else torch.float32,
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).to(device)
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return bert
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@ -269,9 +269,21 @@ def nonen_clean_text_inf(text, language):
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else:
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textlist=[]
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langlist=[]
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mix = ""
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for tmp in LangSegment.getTexts(text):
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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if tmp["lang"] in {"zh","en"}:
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mix += tmp["text"]
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else:
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if mix:
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langlist.append("zh")
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textlist.append(mix)
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mix = ""
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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if mix:
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langlist.append("zh")
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textlist.append(mix)
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mix = ""
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print(textlist)
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print(langlist)
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phones_list = []
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@ -325,19 +337,19 @@ def get_first(text):
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def get_cleaned_text_fianl(text,language):
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if language in {"en","all_zh","all_ja"}:
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if language in {"en","all_zh","all_ja","zh"}:
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phones, word2ph, norm_text = clean_text_inf(text, language)
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elif language in {"zh", "ja","auto"}:
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elif language in {"ja","auto"}:
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phones, word2ph, norm_text = nonen_clean_text_inf(text, language)
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return phones, word2ph, norm_text
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def get_bert_final(phones, word2ph, norm_text,language,device):
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if text_language == "en":
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if text_language in {"en","all_zh","zh"}:
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bert = get_bert_inf(phones, word2ph, norm_text, text_language)
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elif text_language in {"zh", "ja","auto"}:
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elif text_language in {"ja","auto"}:
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bert = nonen_get_bert_inf(text, text_language)
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elif text_language == "all_zh":
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bert = get_bert_feature(norm_text, word2ph).to(device)
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# elif text_language == "all_zh":
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# bert = get_bert_feature(norm_text, word2ph).to(device)
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else:
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bert = torch.zeros((1024, len(phones))).to(device)
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return bert
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@ -1,4 +1,221 @@
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from text import chinese, japanese, cleaned_text_to_sequence, symbols, english
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import ttsfrd
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import re,os,zipfile,requests
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ENG_LANG_MAPPING = {
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"PinYin": "zh-cn",
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"English": "en-us",
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"British": "en-gb",
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"ZhHK": "hk_cantonese",
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"Sichuan": "sichuan",
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"Japanese": "japanese",
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"WuuShangHai": "shanghai",
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"Indonesian": "indonesian",
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"Malay": "malay",
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"Filipino": "filipino",
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"Vietnamese": "vietnamese",
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"Korean": "korean",
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"Russian": "russian",
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}
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chinese_dict = {
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"xx":"x",
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"uei":"ui",
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"ii":"i0",
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"ih":"ir",
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"uen":"un",
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"iou":"iu",
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"angr":"ang",
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"anr":"an",
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"aor":"ao",
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"ar":"a",
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"eir":"ei",
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"engr":"eng",
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"enr":"en",
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"ianr":"ian",
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"iaor":"iao",
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"ingr":"ing",
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"or":"o",
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"ur":"u",
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"ihr":"ih",
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"ongr":"ong",
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"our":"ou",
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"uangr":"uang",
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"uanr":"uan",
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"ueir":"uei",
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"uenr":"uen",
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"uor":"uo",
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"iir":"ii",
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"air":"ai",
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"ier":"ie",
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"uair":"uai",
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"uar":"ua",
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"iar":"ia",
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"inr":"in",
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"iour":"iou",
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"vanr":"van",
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"ver":"ve",
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"vnr":"vn",
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"iangr":"iang",
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"vr":"v",
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"iongr":"iong",
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}
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english_dict = {
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"DH1":"DH",
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"NG0":"NG",
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"SH0":"SH",
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"NG1":"NG",
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"CH0":"CH",
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"HH0":"HH",
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"ZH0":"ZH",
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"HH1":"HH",
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"SH1":"SH",
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"ZH1":"ZH",
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"DH0":"DH",
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"TH1":"TH",
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"CH1":"CH",
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"JH1":"JH",
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"JH0":"JH",
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"NG2":"NG",
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"TH0":"TH",
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}
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japanese_dict = {
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"nn":"N",
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"ux":"U",
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"ix":"I",
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}
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resource_dir = "GPT_SoVITS/text/resource"
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resources_zip_file = "GPT_SoVITS/text/resource.zip"
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if not os.path.exists(resource_dir):
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if not os.path.exists(resources_zip_file):
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print("Downloading ttsfrd resources...")
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modelscope_url = "https://www.modelscope.cn/api/v1/models/speech_tts/speech_kantts_ttsfrd/repo?Revision=v0.0.1&FilePath=resource.zip"
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with requests.get(modelscope_url, stream=True) as r:
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r.raise_for_status()
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with open(resources_zip_file, 'wb') as f:
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for chunk in r.iter_content(chunk_size=8192):
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if chunk:
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f.write(chunk)
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print("Extracting ttsfrd resources...")
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with zipfile.ZipFile(resources_zip_file, "r") as zip_ref:
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zip_ref.extractall("GPT_SoVITS/text")
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fe = ttsfrd.TtsFrontendEngine()
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assert fe.initialize(resource_dir),"Check ttsfrd resource"
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def clean_text(text, language):
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if(language not in language_module_map):
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language="en"
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text=" "
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if language == "zh":
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phones = []
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word2ph = []
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count = 0
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fe.set_lang_type(ENG_LANG_MAPPING["PinYin"])
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res = fe.gen_tacotron_symbols(text)
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matches = re.findall(r'\{(.*?)\}', res)
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for match in matches:
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elements = match.split("$")
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if elements[2] == "s_none":
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if elements[0] == "#4":
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phone = "."
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phones += [phone]
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word2ph.append(1)
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continue
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if elements[0] == "#3":
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phone = ","
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phones += [phone]
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word2ph.append(1)
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continue
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# Chinese
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if elements[0] == "ga":
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phone = "AA"
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phones += [phone]
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count += 1
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continue
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if elements[0] == "ge":
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phone = "EE"
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phones += [phone]
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count += 1
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continue
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if elements[0] == "go":
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phone = "OO"
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phones += [phone]
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count += 1
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continue
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if "_c" in elements[0]:
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if elements[2] in ("s_begin","s_middle","s_both","s_end"):
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phone = elements[0].replace("_c", "")
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phone = chinese_dict.get(phone, phone)
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phone = chinese_dict.get(phone, phone)
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count += 1
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if elements[2] == "s_end":
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phone += elements[1].replace("tone", "")
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word2ph.append(count)
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count = 0
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phones += [phone]
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continue
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# English
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else:
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if elements[2] in ("s_begin","s_middle","s_both","s_end"):
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phone = elements[0].upper()
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if len(elements[0]) > 1 :
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phone += elements[1].replace("tone", "")
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phone = english_dict.get(phone, phone)
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phones += [phone]
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continue
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elif language == "en":
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phones = []
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word2ph = None
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fe.set_lang_type(ENG_LANG_MAPPING["English"])
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res = fe.gen_tacotron_symbols(text)
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matches = re.findall(r'\{(.*?)\}', res)
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for match in matches:
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elements = match.split("$")
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if elements[2] == "s_none":
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if elements[0] == "#4":
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phone = "."
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phones += [phone]
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continue
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if elements[2] in ("s_begin","s_middle","s_both","s_end"):
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phone = elements[0].upper()
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if len(elements[0]) > 1 :
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phone += elements[1].replace("tone", "")
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phone = english_dict.get(phone, phone)
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phones += [phone]
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continue
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elif language == "ja":
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phones = []
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word2ph = None
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fe.set_lang_type(ENG_LANG_MAPPING["Japanese"])
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res = fe.gen_tacotron_symbols(text)
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matches = re.findall(r'\{(.*?)\}', res)
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for match in matches:
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elements = match.split("$")
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if elements[2] == "s_none":
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if elements[0] == "#4":
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phone = "."
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phones += [phone]
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continue
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if elements[0] == "#3":
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phone = ","
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phones += [phone]
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continue
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if elements[2] in ("s_begin","s_middle","s_both","s_end"):
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phone = elements[0]
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phone = japanese_dict.get(phone, phone)
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phones += [phone]
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continue
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# print("new:",phones)
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# p,w,n = clean_text_old(text, language)
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# print("old:",p)
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return phones, word2ph, text
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language_module_map = {"zh": chinese, "ja": japanese, "en": english}
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special = [
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@ -9,7 +226,7 @@ special = [
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]
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def clean_text(text, language):
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def clean_text_old(text, language):
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if(language not in language_module_map):
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language="en"
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text=" "
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