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| import sys | |
| sys.path.insert(0, "GPT_SoVITS") | |
| from text import cleaned_text_to_sequence | |
| from text.cleaner import clean_text | |
| import LangSegment | |
| import re | |
| splits = {"，", "。", "？", "！", ",", ".", "?", "!", "~", ":", "：", "—", "…", } | |
| def clean_text_inf(text, language): | |
| phones, word2ph, norm_text = clean_text(text, language) | |
| phones = cleaned_text_to_sequence(phones) | |
| return phones, word2ph, norm_text | |
| def get_first(text): | |
| pattern = "[" + "".join(re.escape(sep) for sep in splits) + "]" | |
| text = re.split(pattern, text)[0].strip() | |
| return text | |
| def splite_en_inf(sentence, language): | |
| """ | |
| Split the input sentence into a list of text segments and language tags. | |
| Args: | |
| sentence (str): The input sentence to be split. | |
| language (str): The language tag of the input sentence. | |
| Returns: | |
| tuple: A tuple containing two lists - textlist and langlist. | |
| - textlist: A list of text segments extracted from the input sentence. | |
| - langlist: A list of language tags corresponding to each text segment. | |
| """ | |
| pattern = re.compile(r'[a-zA-Z ]+') | |
| textlist = [] | |
| langlist = [] | |
| pos = 0 | |
| for match in pattern.finditer(sentence): | |
| start, end = match.span() | |
| if start > pos: | |
| textlist.append(sentence[pos:start]) | |
| langlist.append(language) | |
| textlist.append(sentence[start:end]) | |
| langlist.append("en") | |
| pos = end | |
| if pos < len(sentence): | |
| textlist.append(sentence[pos:]) | |
| langlist.append(language) | |
| # Merge punctuation into previous word | |
| for i in range(len(textlist)-1, 0, -1): | |
| if re.match(r'^[\W_]+$', textlist[i]): | |
| textlist[i-1] += textlist[i] | |
| del textlist[i] | |
| del langlist[i] | |
| # Merge consecutive words with the same language tag | |
| i = 0 | |
| while i < len(langlist) - 1: | |
| if langlist[i] == langlist[i+1]: | |
| textlist[i] += textlist[i+1] | |
| del textlist[i+1] | |
| del langlist[i+1] | |
| else: | |
| i += 1 | |
| return textlist, langlist | |
| def merge_short_text_in_array(texts, threshold): | |
| if (len(texts)) < 2: | |
| return texts | |
| result = [] | |
| text = "" | |
| for ele in texts: | |
| text += ele | |
| if len(text) >= threshold: | |
| result.append(text) | |
| text = "" | |
| if (len(text) > 0): | |
| if len(result) == 0: | |
| result.append(text) | |
| else: | |
| result[len(result) - 1] += text | |
| return result | |
| def auto_cut(inp): | |
| # if not re.search(r'[^\w\s]', inp[-1]): | |
| # inp += '。' | |
| inp = inp.strip("\n") | |
| split_punds = r'[?!。？！~：]' | |
| if inp[-1] not in split_punds: | |
| inp+="。" | |
| items = re.split(f'({split_punds})', inp) | |
| items = ["".join(group) for group in zip(items[::2], items[1::2])] | |
| def process_commas(text): | |
| separators = ['，', ',', '、', '——', '…'] | |
| count = 0 | |
| processed_text = "" | |
| for char in text: | |
| processed_text += char | |
| if char in separators: | |
| if count > 12: | |
| processed_text += '\n' | |
| count = 0 | |
| else: | |
| count += 1 # 对于非分隔符字符，增加计数 | |
| return processed_text | |
| final_items=[process_commas(item) for item in items] | |
| return "\n".join(final_items) | |