From 6df61f58e4d18d4c2ad9d1eddd6a1bd690034c23 Mon Sep 17 00:00:00 2001 From: KamioRinn <63162909+KamioRinn@users.noreply.github.com> Date: Fri, 27 Jun 2025 11:58:41 +0800 Subject: [PATCH] =?UTF-8?q?=E8=AF=AD=E8=A8=80=E5=88=86=E5=89=B2=E5=8F=8A?= =?UTF-8?q?=E6=A0=BC=E5=BC=8F=E5=8C=96=E4=BC=98=E5=8C=96=20(#2488)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * better LangSegmenter * add version num2str * better version num2str * sync fast infer * sync api * remove duplicate spaces * remove unnecessary code --------- Co-authored-by: RVC-Boss <129054828+RVC-Boss@users.noreply.github.com> --- GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 126 +++++------ GPT_SoVITS/inference_webui.py | 121 +++++----- .../text/LangSegmenter/langsegmenter.py | 209 +++++++++++------- GPT_SoVITS/text/chinese.py | 14 -- GPT_SoVITS/text/chinese2.py | 14 -- GPT_SoVITS/text/zh_normalization/num.py | 24 +- .../zh_normalization/text_normlization.py | 3 + api.py | 117 +++++----- 8 files changed, 332 insertions(+), 296 deletions(-) diff --git a/GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py b/GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py index 9a478d4..283e91c 100644 --- a/GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py +++ b/GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py @@ -121,71 +121,67 @@ class TextPreprocessor: def get_phones_and_bert(self, text: str, language: str, version: str, final: bool = False): with self.bert_lock: - if language in {"en", "all_zh", "all_ja", "all_ko", "all_yue"}: - # language = language.replace("all_","") - formattext = text - while " " in formattext: - formattext = formattext.replace(" ", " ") - if language == "all_zh": - if re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return self.get_phones_and_bert(formattext, "zh", version) + text = re.sub(r' {2,}', ' ', text) + textlist = [] + langlist = [] + if language == "all_zh": + for tmp in LangSegmenter.getTexts(text,"zh"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_yue": + for tmp in LangSegmenter.getTexts(text,"zh"): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ja": + for tmp in LangSegmenter.getTexts(text,"ja"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ko": + for tmp in LangSegmenter.getTexts(text,"ko"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "en": + langlist.append("en") + textlist.append(text) + elif language == "auto": + for tmp in LangSegmenter.getTexts(text): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "auto_yue": + for tmp in LangSegmenter.getTexts(text): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + else: + for tmp in LangSegmenter.getTexts(text): + if langlist: + if (tmp["lang"] == "en" and langlist[-1] == "en") or (tmp["lang"] != "en" and langlist[-1] != "en"): + textlist[-1] += tmp["text"] + continue + if tmp["lang"] == "en": + langlist.append(tmp["lang"]) else: - phones, word2ph, norm_text = self.clean_text_inf(formattext, language, version) - bert = self.get_bert_feature(norm_text, word2ph).to(self.device) - elif language == "all_yue" and re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return self.get_phones_and_bert(formattext, "yue", version) - else: - phones, word2ph, norm_text = self.clean_text_inf(formattext, language, version) - bert = torch.zeros( - (1024, len(phones)), - dtype=torch.float32, - ).to(self.device) - elif language in {"zh", "ja", "ko", "yue", "auto", "auto_yue"}: - textlist = [] - langlist = [] - if language == "auto": - for tmp in LangSegmenter.getTexts(text): - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - elif language == "auto_yue": - for tmp in LangSegmenter.getTexts(text): - if tmp["lang"] == "zh": - tmp["lang"] = "yue" - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - else: - for tmp in LangSegmenter.getTexts(text): - if langlist: - if (tmp["lang"] == "en" and langlist[-1] == "en") or ( - tmp["lang"] != "en" and langlist[-1] != "en" - ): - textlist[-1] += tmp["text"] - continue - if tmp["lang"] == "en": - langlist.append(tmp["lang"]) - else: - # 因无法区别中日韩文汉字,以用户输入为准 - langlist.append(language) - textlist.append(tmp["text"]) - # print(textlist) - # print(langlist) - phones_list = [] - bert_list = [] - norm_text_list = [] - for i in range(len(textlist)): - lang = langlist[i] - phones, word2ph, norm_text = self.clean_text_inf(textlist[i], lang, version) - bert = self.get_bert_inf(phones, word2ph, norm_text, lang) - phones_list.append(phones) - norm_text_list.append(norm_text) - bert_list.append(bert) - bert = torch.cat(bert_list, dim=1) - phones = sum(phones_list, []) - norm_text = "".join(norm_text_list) + # 因无法区别中日韩文汉字,以用户输入为准 + langlist.append(language) + textlist.append(tmp["text"]) + # print(textlist) + # print(langlist) + phones_list = [] + bert_list = [] + norm_text_list = [] + for i in range(len(textlist)): + lang = langlist[i] + phones, word2ph, norm_text = self.clean_text_inf(textlist[i], lang, version) + bert = self.get_bert_inf(phones, word2ph, norm_text, lang) + phones_list.append(phones) + norm_text_list.append(norm_text) + bert_list.append(bert) + bert = torch.cat(bert_list, dim=1) + phones = sum(phones_list, []) + norm_text = "".join(norm_text_list) if not final and len(phones) < 6: return self.get_phones_and_bert("." + text, language, version, final=True) @@ -240,4 +236,4 @@ class TextPreprocessor: punctuations = "".join(re.escape(p) for p in punctuation) pattern = f"([{punctuations}])([{punctuations}])+" result = re.sub(pattern, r"\1", text) - return result + return result \ No newline at end of file diff --git a/GPT_SoVITS/inference_webui.py b/GPT_SoVITS/inference_webui.py index 5c7d010..643e405 100644 --- a/GPT_SoVITS/inference_webui.py +++ b/GPT_SoVITS/inference_webui.py @@ -586,68 +586,67 @@ from text import chinese def get_phones_and_bert(text, language, version, final=False): - if language in {"en", "all_zh", "all_ja", "all_ko", "all_yue"}: - formattext = text - while " " in formattext: - formattext = formattext.replace(" ", " ") - if language == "all_zh": - if re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return get_phones_and_bert(formattext, "zh", version) + text = re.sub(r' {2,}', ' ', text) + textlist = [] + langlist = [] + if language == "all_zh": + for tmp in LangSegmenter.getTexts(text,"zh"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_yue": + for tmp in LangSegmenter.getTexts(text,"zh"): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ja": + for tmp in LangSegmenter.getTexts(text,"ja"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ko": + for tmp in LangSegmenter.getTexts(text,"ko"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "en": + langlist.append("en") + textlist.append(text) + elif language == "auto": + for tmp in LangSegmenter.getTexts(text): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "auto_yue": + for tmp in LangSegmenter.getTexts(text): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + else: + for tmp in LangSegmenter.getTexts(text): + if langlist: + if (tmp["lang"] == "en" and langlist[-1] == "en") or (tmp["lang"] != "en" and langlist[-1] != "en"): + textlist[-1] += tmp["text"] + continue + if tmp["lang"] == "en": + langlist.append(tmp["lang"]) else: - phones, word2ph, norm_text = clean_text_inf(formattext, language, version) - bert = get_bert_feature(norm_text, word2ph).to(device) - elif language == "all_yue" and re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return get_phones_and_bert(formattext, "yue", version) - else: - phones, word2ph, norm_text = clean_text_inf(formattext, language, version) - bert = torch.zeros( - (1024, len(phones)), - dtype=torch.float16 if is_half == True else torch.float32, - ).to(device) - elif language in {"zh", "ja", "ko", "yue", "auto", "auto_yue"}: - textlist = [] - langlist = [] - if language == "auto": - for tmp in LangSegmenter.getTexts(text): - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - elif language == "auto_yue": - for tmp in LangSegmenter.getTexts(text): - if tmp["lang"] == "zh": - tmp["lang"] = "yue" - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - else: - for tmp in LangSegmenter.getTexts(text): - if langlist: - if (tmp["lang"] == "en" and langlist[-1] == "en") or (tmp["lang"] != "en" and langlist[-1] != "en"): - textlist[-1] += tmp["text"] - continue - if tmp["lang"] == "en": - langlist.append(tmp["lang"]) - else: - # 因无法区别中日韩文汉字,以用户输入为准 - langlist.append(language) - textlist.append(tmp["text"]) - print(textlist) - print(langlist) - phones_list = [] - bert_list = [] - norm_text_list = [] - for i in range(len(textlist)): - lang = langlist[i] - phones, word2ph, norm_text = clean_text_inf(textlist[i], lang, version) - bert = get_bert_inf(phones, word2ph, norm_text, lang) - phones_list.append(phones) - norm_text_list.append(norm_text) - bert_list.append(bert) - bert = torch.cat(bert_list, dim=1) - phones = sum(phones_list, []) - norm_text = "".join(norm_text_list) + # 因无法区别中日韩文汉字,以用户输入为准 + langlist.append(language) + textlist.append(tmp["text"]) + print(textlist) + print(langlist) + phones_list = [] + bert_list = [] + norm_text_list = [] + for i in range(len(textlist)): + lang = langlist[i] + phones, word2ph, norm_text = clean_text_inf(textlist[i], lang, version) + bert = get_bert_inf(phones, word2ph, norm_text, lang) + phones_list.append(phones) + norm_text_list.append(norm_text) + bert_list.append(bert) + bert = torch.cat(bert_list, dim=1) + phones = sum(phones_list, []) + norm_text = "".join(norm_text_list) if not final and len(phones) < 6: return get_phones_and_bert("." + text, language, version, final=True) diff --git a/GPT_SoVITS/text/LangSegmenter/langsegmenter.py b/GPT_SoVITS/text/LangSegmenter/langsegmenter.py index 0187ea6..99b3a42 100644 --- a/GPT_SoVITS/text/LangSegmenter/langsegmenter.py +++ b/GPT_SoVITS/text/LangSegmenter/langsegmenter.py @@ -3,44 +3,38 @@ import re # jieba静音 import jieba - jieba.setLogLevel(logging.CRITICAL) # 更改fast_langdetect大模型位置 from pathlib import Path import fast_langdetect - -fast_langdetect.infer._default_detector = fast_langdetect.infer.LangDetector( - fast_langdetect.infer.LangDetectConfig( - cache_dir=Path(__file__).parent.parent.parent / "pretrained_models" / "fast_langdetect" - ) -) +fast_langdetect.infer._default_detector = fast_langdetect.infer.LangDetector(fast_langdetect.infer.LangDetectConfig(cache_dir=Path(__file__).parent.parent.parent / "pretrained_models" / "fast_langdetect")) from split_lang import LangSplitter def full_en(text): - pattern = r"^(?=.*[A-Za-z])[A-Za-z0-9\s\u0020-\u007E\u2000-\u206F\u3000-\u303F\uFF00-\uFFEF]+$" + pattern = r'^(?=.*[A-Za-z])[A-Za-z0-9\s\u0020-\u007E\u2000-\u206F\u3000-\u303F\uFF00-\uFFEF]+$' return bool(re.match(pattern, text)) def full_cjk(text): # 来自wiki cjk_ranges = [ - (0x4E00, 0x9FFF), # CJK Unified Ideographs - (0x3400, 0x4DB5), # CJK Extension A - (0x20000, 0x2A6DD), # CJK Extension B - (0x2A700, 0x2B73F), # CJK Extension C - (0x2B740, 0x2B81F), # CJK Extension D - (0x2B820, 0x2CEAF), # CJK Extension E - (0x2CEB0, 0x2EBEF), # CJK Extension F - (0x30000, 0x3134A), # CJK Extension G - (0x31350, 0x323AF), # CJK Extension H - (0x2EBF0, 0x2EE5D), # CJK Extension H + (0x4E00, 0x9FFF), # CJK Unified Ideographs + (0x3400, 0x4DB5), # CJK Extension A + (0x20000, 0x2A6DD), # CJK Extension B + (0x2A700, 0x2B73F), # CJK Extension C + (0x2B740, 0x2B81F), # CJK Extension D + (0x2B820, 0x2CEAF), # CJK Extension E + (0x2CEB0, 0x2EBEF), # CJK Extension F + (0x30000, 0x3134A), # CJK Extension G + (0x31350, 0x323AF), # CJK Extension H + (0x2EBF0, 0x2EE5D), # CJK Extension H ] - pattern = r"[0-9、-〜。！？.!?… /]+$" + pattern = r'[0-9、-〜。！？.!?… /]+$' cjk_text = "" for char in text: @@ -51,7 +45,7 @@ def full_cjk(text): return cjk_text -def split_jako(tag_lang, item): +def split_jako(tag_lang,item): if tag_lang == "ja": pattern = r"([\u3041-\u3096\u3099\u309A\u30A1-\u30FA\u30FC]+(?:[0-9、-〜。！？.!?… ]+[\u3041-\u3096\u3099\u309A\u30A1-\u30FA\u30FC]*)*)" else: @@ -59,118 +53,165 @@ def split_jako(tag_lang, item): lang_list: list[dict] = [] tag = 0 - for match in re.finditer(pattern, item["text"]): + for match in re.finditer(pattern, item['text']): if match.start() > tag: - lang_list.append({"lang": item["lang"], "text": item["text"][tag : match.start()]}) + lang_list.append({'lang':item['lang'],'text':item['text'][tag:match.start()]}) tag = match.end() - lang_list.append({"lang": tag_lang, "text": item["text"][match.start() : match.end()]}) + lang_list.append({'lang':tag_lang,'text':item['text'][match.start():match.end()]}) - if tag < len(item["text"]): - lang_list.append({"lang": item["lang"], "text": item["text"][tag : len(item["text"])]}) + if tag < len(item['text']): + lang_list.append({'lang':item['lang'],'text':item['text'][tag:len(item['text'])]}) return lang_list def merge_lang(lang_list, item): - if lang_list and item["lang"] == lang_list[-1]["lang"]: - lang_list[-1]["text"] += item["text"] + if lang_list and item['lang'] == lang_list[-1]['lang']: + lang_list[-1]['text'] += item['text'] else: lang_list.append(item) return lang_list -class LangSegmenter: +class LangSegmenter(): # 默认过滤器, 基于gsv目前四种语言 DEFAULT_LANG_MAP = { "zh": "zh", "yue": "zh", # 粤语 "wuu": "zh", # 吴语 "zh-cn": "zh", - "zh-tw": "x", # 繁体设置为x + "zh-tw": "x", # 繁体设置为x "ko": "ko", "ja": "ja", "en": "en", } - def getTexts(text): + def getTexts(text,default_lang = ""): lang_splitter = LangSplitter(lang_map=LangSegmenter.DEFAULT_LANG_MAP) + lang_splitter.merge_across_digit = False substr = lang_splitter.split_by_lang(text=text) lang_list: list[dict] = [] - for _, item in enumerate(substr): - dict_item = {"lang": item.lang, "text": item.text} + have_num = False - # 处理短英文被识别为其他语言的问题 - if full_en(dict_item["text"]): - dict_item["lang"] = "en" - lang_list = merge_lang(lang_list, dict_item) + for _, item in enumerate(substr): + dict_item = {'lang':item.lang,'text':item.text} + + if dict_item['lang'] == 'digit': + if default_lang != "": + dict_item['lang'] = default_lang + else: + have_num = True + lang_list = merge_lang(lang_list,dict_item) continue - # 处理非日语夹日文的问题(不包含CJK) - ja_list: list[dict] = [] - if dict_item["lang"] != "ja": - ja_list = split_jako("ja", dict_item) + # 处理短英文被识别为其他语言的问题 + if full_en(dict_item['text']): + dict_item['lang'] = 'en' + lang_list = merge_lang(lang_list,dict_item) + continue - if not ja_list: - ja_list.append(dict_item) + if default_lang != "": + dict_item['lang'] = default_lang + lang_list = merge_lang(lang_list,dict_item) + continue + else: + # 处理非日语夹日文的问题(不包含CJK) + ja_list: list[dict] = [] + if dict_item['lang'] != 'ja': + ja_list = split_jako('ja',dict_item) - # 处理非韩语夹韩语的问题(不包含CJK) - ko_list: list[dict] = [] - temp_list: list[dict] = [] - for _, ko_item in enumerate(ja_list): - if ko_item["lang"] != "ko": - ko_list = split_jako("ko", ko_item) + if not ja_list: + ja_list.append(dict_item) - if ko_list: - temp_list.extend(ko_list) - else: - temp_list.append(ko_item) + # 处理非韩语夹韩语的问题(不包含CJK) + ko_list: list[dict] = [] + temp_list: list[dict] = [] + for _, ko_item in enumerate(ja_list): + if ko_item["lang"] != 'ko': + ko_list = split_jako('ko',ko_item) - # 未存在非日韩文夹日韩文 - if len(temp_list) == 1: - # 未知语言检查是否为CJK - if dict_item["lang"] == "x": - cjk_text = full_cjk(dict_item["text"]) - if cjk_text: - dict_item = {"lang": "zh", "text": cjk_text} - lang_list = merge_lang(lang_list, dict_item) + if ko_list: + temp_list.extend(ko_list) else: - lang_list = merge_lang(lang_list, dict_item) - continue - else: - lang_list = merge_lang(lang_list, dict_item) - continue + temp_list.append(ko_item) - # 存在非日韩文夹日韩文 - for _, temp_item in enumerate(temp_list): - # 未知语言检查是否为CJK - if temp_item["lang"] == "x": - cjk_text = full_cjk(dict_item["text"]) - if cjk_text: - dict_item = {"lang": "zh", "text": cjk_text} - lang_list = merge_lang(lang_list, dict_item) + # 未存在非日韩文夹日韩文 + if len(temp_list) == 1: + # 未知语言检查是否为CJK + if dict_item['lang'] == 'x': + cjk_text = full_cjk(dict_item['text']) + if cjk_text: + dict_item = {'lang':'zh','text':cjk_text} + lang_list = merge_lang(lang_list,dict_item) + else: + lang_list = merge_lang(lang_list,dict_item) + continue else: - lang_list = merge_lang(lang_list, dict_item) - else: - lang_list = merge_lang(lang_list, temp_item) + lang_list = merge_lang(lang_list,dict_item) + continue + # 存在非日韩文夹日韩文 + for _, temp_item in enumerate(temp_list): + # 未知语言检查是否为CJK + if temp_item['lang'] == 'x': + cjk_text = full_cjk(temp_item['text']) + if cjk_text: + lang_list = merge_lang(lang_list,{'lang':'zh','text':cjk_text}) + else: + lang_list = merge_lang(lang_list,temp_item) + else: + lang_list = merge_lang(lang_list,temp_item) + + # 有数字 + if have_num: + temp_list = lang_list + lang_list = [] + for i, temp_item in enumerate(temp_list): + if temp_item['lang'] == 'digit': + if default_lang: + temp_item['lang'] = default_lang + elif lang_list and i == len(temp_list) - 1: + temp_item['lang'] = lang_list[-1]['lang'] + elif not lang_list and i < len(temp_list) - 1: + temp_item['lang'] = temp_list[1]['lang'] + elif lang_list and i < len(temp_list) - 1: + if lang_list[-1]['lang'] == temp_list[i + 1]['lang']: + temp_item['lang'] = lang_list[-1]['lang'] + elif lang_list[-1]['text'][-1] in [",",".","!","?","，","。","！","？"]: + temp_item['lang'] = temp_list[i + 1]['lang'] + elif temp_list[i + 1]['text'][0] in [",",".","!","?","，","。","！","？"]: + temp_item['lang'] = lang_list[-1]['lang'] + elif temp_item['text'][-1] in ["。","."]: + temp_item['lang'] = lang_list[-1]['lang'] + elif len(lang_list[-1]['text']) >= len(temp_list[i + 1]['text']): + temp_item['lang'] = lang_list[-1]['lang'] + else: + temp_item['lang'] = temp_list[i + 1]['lang'] + else: + temp_item['lang'] = 'zh' + + lang_list = merge_lang(lang_list,temp_item) + + + # 筛X temp_list = lang_list lang_list = [] for _, temp_item in enumerate(temp_list): - if temp_item["lang"] == "x": + if temp_item['lang'] == 'x': if lang_list: - temp_item["lang"] = lang_list[-1]["lang"] + temp_item['lang'] = lang_list[-1]['lang'] elif len(temp_list) > 1: - temp_item["lang"] = temp_list[1]["lang"] + temp_item['lang'] = temp_list[1]['lang'] else: - temp_item["lang"] = "zh" + temp_item['lang'] = 'zh' - lang_list = merge_lang(lang_list, temp_item) + lang_list = merge_lang(lang_list,temp_item) return lang_list - + if __name__ == "__main__": text = "MyGO?,你也喜欢まいご吗？" @@ -178,3 +219,7 @@ if __name__ == "__main__": text = "ねえ、知ってる？最近、僕は天文学を勉強してるんだ。君の瞳が星空みたいにキラキラしてるからさ。" print(LangSegmenter.getTexts(text)) + + text = "当时ThinkPad T60刚刚发布，一同推出的还有一款名为Advanced Dock的扩展坞配件。这款扩展坞通过连接T60底部的插槽，扩展出包括PCIe在内的一大堆接口，并且自带电源，让T60可以安装桌面显卡来提升性能。" + print(LangSegmenter.getTexts(text,"zh")) + print(LangSegmenter.getTexts(text)) \ No newline at end of file diff --git a/GPT_SoVITS/text/chinese.py b/GPT_SoVITS/text/chinese.py index ce44215..944c9cb 100644 --- a/GPT_SoVITS/text/chinese.py +++ b/GPT_SoVITS/text/chinese.py @@ -181,20 +181,6 @@ def text_normalize(text): return dest_text -# 不排除英文的文本格式化 -def mix_text_normalize(text): - # https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization - tx = TextNormalizer() - sentences = tx.normalize(text) - dest_text = "" - for sentence in sentences: - dest_text += replace_punctuation_with_en(sentence) - - # 避免重复标点引起的参考泄露 - dest_text = replace_consecutive_punctuation(dest_text) - return dest_text - - if __name__ == "__main__": text = "啊——但是《原神》是由,米哈\游自主，研发的一款全.新开放世界.冒险游戏" text = "呣呣呣～就是…大人的鼹鼠党吧？" diff --git a/GPT_SoVITS/text/chinese2.py b/GPT_SoVITS/text/chinese2.py index 612aa3a..dcce0d9 100644 --- a/GPT_SoVITS/text/chinese2.py +++ b/GPT_SoVITS/text/chinese2.py @@ -326,20 +326,6 @@ def text_normalize(text): return dest_text -# 不排除英文的文本格式化 -def mix_text_normalize(text): - # https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization - tx = TextNormalizer() - sentences = tx.normalize(text) - dest_text = "" - for sentence in sentences: - dest_text += replace_punctuation_with_en(sentence) - - # 避免重复标点引起的参考泄露 - dest_text = replace_consecutive_punctuation(dest_text) - return dest_text - - if __name__ == "__main__": text = "啊——但是《原神》是由,米哈\游自主，研发的一款全.新开放世界.冒险游戏" text = "呣呣呣～就是…大人的鼹鼠党吧？" diff --git a/GPT_SoVITS/text/zh_normalization/num.py b/GPT_SoVITS/text/zh_normalization/num.py index c3af4d6..14d602b 100644 --- a/GPT_SoVITS/text/zh_normalization/num.py +++ b/GPT_SoVITS/text/zh_normalization/num.py @@ -256,6 +256,24 @@ def replace_to_range(match) -> str: return result +RE_VERSION_NUM = re.compile(r"((\d+)(\.\d+)(\.\d+)?(\.\d+)+)") +def replace_vrsion_num(match) -> str: + """ + Args: + match (re.Match) + Returns: + str + """ + result = "" + for c in match.group(1): + if c == ".": + result += "点" + else: + result += num2str(c) + return result + + + def _get_value(value_string: str, use_zero: bool = True) -> List[str]: stripped = value_string.lstrip("0") if len(stripped) == 0: @@ -308,7 +326,11 @@ def num2str(value_string: str) -> str: result = verbalize_cardinal(integer) - decimal = decimal.rstrip("0") + if decimal.endswith("0"): + decimal = decimal.rstrip("0") + "0" + else: + decimal = decimal.rstrip("0") + if decimal: # '.22' is verbalized as '零点二二' # '3.20' is verbalized as '三点二 diff --git a/GPT_SoVITS/text/zh_normalization/text_normlization.py b/GPT_SoVITS/text/zh_normalization/text_normlization.py index 099b01b..1a6cdd0 100644 --- a/GPT_SoVITS/text/zh_normalization/text_normlization.py +++ b/GPT_SoVITS/text/zh_normalization/text_normlization.py @@ -25,6 +25,7 @@ from .chronology import replace_time from .constants import F2H_ASCII_LETTERS from .constants import F2H_DIGITS from .constants import F2H_SPACE +from .num import RE_VERSION_NUM from .num import RE_DECIMAL_NUM from .num import RE_DEFAULT_NUM from .num import RE_FRAC @@ -36,6 +37,7 @@ from .num import RE_RANGE from .num import RE_TO_RANGE from .num import RE_ASMD from .num import RE_POWER +from .num import replace_vrsion_num from .num import replace_default_num from .num import replace_frac from .num import replace_negative_num @@ -158,6 +160,7 @@ class TextNormalizer: sentence = RE_RANGE.sub(replace_range, sentence) sentence = RE_INTEGER.sub(replace_negative_num, sentence) + sentence = RE_VERSION_NUM.sub(replace_vrsion_num, sentence) sentence = RE_DECIMAL_NUM.sub(replace_number, sentence) sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier, sentence) sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence) diff --git a/api.py b/api.py index dc2e882..cc0896a 100644 --- a/api.py +++ b/api.py @@ -543,66 +543,65 @@ from text import chinese def get_phones_and_bert(text, language, version, final=False): - if language in {"en", "all_zh", "all_ja", "all_ko", "all_yue"}: - formattext = text - while " " in formattext: - formattext = formattext.replace(" ", " ") - if language == "all_zh": - if re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return get_phones_and_bert(formattext, "zh", version) + text = re.sub(r' {2,}', ' ', text) + textlist = [] + langlist = [] + if language == "all_zh": + for tmp in LangSegmenter.getTexts(text,"zh"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_yue": + for tmp in LangSegmenter.getTexts(text,"zh"): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ja": + for tmp in LangSegmenter.getTexts(text,"ja"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "all_ko": + for tmp in LangSegmenter.getTexts(text,"ko"): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "en": + langlist.append("en") + textlist.append(text) + elif language == "auto": + for tmp in LangSegmenter.getTexts(text): + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + elif language == "auto_yue": + for tmp in LangSegmenter.getTexts(text): + if tmp["lang"] == "zh": + tmp["lang"] = "yue" + langlist.append(tmp["lang"]) + textlist.append(tmp["text"]) + else: + for tmp in LangSegmenter.getTexts(text): + if langlist: + if (tmp["lang"] == "en" and langlist[-1] == "en") or (tmp["lang"] != "en" and langlist[-1] != "en"): + textlist[-1] += tmp["text"] + continue + if tmp["lang"] == "en": + langlist.append(tmp["lang"]) else: - phones, word2ph, norm_text = clean_text_inf(formattext, language, version) - bert = get_bert_feature(norm_text, word2ph).to(device) - elif language == "all_yue" and re.search(r"[A-Za-z]", formattext): - formattext = re.sub(r"[a-z]", lambda x: x.group(0).upper(), formattext) - formattext = chinese.mix_text_normalize(formattext) - return get_phones_and_bert(formattext, "yue", version) - else: - phones, word2ph, norm_text = clean_text_inf(formattext, language, version) - bert = torch.zeros( - (1024, len(phones)), - dtype=torch.float16 if is_half == True else torch.float32, - ).to(device) - elif language in {"zh", "ja", "ko", "yue", "auto", "auto_yue"}: - textlist = [] - langlist = [] - if language == "auto": - for tmp in LangSegmenter.getTexts(text): - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - elif language == "auto_yue": - for tmp in LangSegmenter.getTexts(text): - if tmp["lang"] == "zh": - tmp["lang"] = "yue" - langlist.append(tmp["lang"]) - textlist.append(tmp["text"]) - else: - for tmp in LangSegmenter.getTexts(text): - if langlist: - if (tmp["lang"] == "en" and langlist[-1] == "en") or (tmp["lang"] != "en" and langlist[-1] != "en"): - textlist[-1] += tmp["text"] - continue - if tmp["lang"] == "en": - langlist.append(tmp["lang"]) - else: - # 因无法区别中日韩文汉字,以用户输入为准 - langlist.append(language) - textlist.append(tmp["text"]) - phones_list = [] - bert_list = [] - norm_text_list = [] - for i in range(len(textlist)): - lang = langlist[i] - phones, word2ph, norm_text = clean_text_inf(textlist[i], lang, version) - bert = get_bert_inf(phones, word2ph, norm_text, lang) - phones_list.append(phones) - norm_text_list.append(norm_text) - bert_list.append(bert) - bert = torch.cat(bert_list, dim=1) - phones = sum(phones_list, []) - norm_text = "".join(norm_text_list) + # 因无法区别中日韩文汉字,以用户输入为准 + langlist.append(language) + textlist.append(tmp["text"]) + phones_list = [] + bert_list = [] + norm_text_list = [] + for i in range(len(textlist)): + lang = langlist[i] + phones, word2ph, norm_text = clean_text_inf(textlist[i], lang, version) + bert = get_bert_inf(phones, word2ph, norm_text, lang) + phones_list.append(phones) + norm_text_list.append(norm_text) + bert_list.append(bert) + bert = torch.cat(bert_list, dim=1) + phones = sum(phones_list, []) + norm_text = "".join(norm_text_list) if not final and len(phones) < 6: return get_phones_and_bert("." + text, language, version, final=True)