From 6deed97efe636bf68825ebb0ec82ec994fd1d42f Mon Sep 17 00:00:00 2001 From: Yrom Date: Wed, 19 Nov 2025 20:46:09 +0800 Subject: [PATCH] feat(indextts): add glossary support for custom term pronunciations --- indextts/infer_v2.py | 8 ++- indextts/utils/common.py | 2 +- indextts/utils/front.py | 120 +++++++++++++++++++++++++++++++-- tools/i18n/locale/en_US.json | 13 +++- webui.py | 125 ++++++++++++++++++++++++++++++++++- 5 files changed, 259 insertions(+), 9 deletions(-) diff --git a/indextts/infer_v2.py b/indextts/infer_v2.py index 5294165..43efc8e 100644 --- a/indextts/infer_v2.py +++ b/indextts/infer_v2.py @@ -167,12 +167,18 @@ class IndexTTS2: print(">> bigvgan weights restored from:", bigvgan_name) self.bpe_path = os.path.join(self.model_dir, self.cfg.dataset["bpe_model"]) - self.normalizer = TextNormalizer() + self.normalizer = TextNormalizer(enable_glossary=True) self.normalizer.load() print(">> TextNormalizer loaded") self.tokenizer = TextTokenizer(self.bpe_path, self.normalizer) print(">> bpe model loaded from:", self.bpe_path) + # 加载术语词汇表（如果存在） + self.glossary_path = os.path.join(self.model_dir, "glossary.yaml") + if os.path.exists(self.glossary_path): + self.normalizer.load_glossary_from_yaml(self.glossary_path) + print(">> Glossary loaded from:", self.glossary_path) + emo_matrix = torch.load(os.path.join(self.model_dir, self.cfg.emo_matrix)) self.emo_matrix = emo_matrix.to(self.device) self.emo_num = list(self.cfg.emo_num) diff --git a/indextts/utils/common.py b/indextts/utils/common.py index eb2f89a..d137e18 100644 --- a/indextts/utils/common.py +++ b/indextts/utils/common.py @@ -62,7 +62,7 @@ def de_tokenized_by_CJK_char(line: str, do_lower_case=False) -> str: output = "see you!" """ # replace english words in the line with placeholders - english_word_pattern = re.compile(r"([A-Z]+(?:[\s-][A-Z-]+)*)", re.IGNORECASE) + english_word_pattern = re.compile(r"([A-Z]+(?:[\s'-][A-Z-]+)*)", re.IGNORECASE) english_sents = english_word_pattern.findall(line) for i, sent in enumerate(english_sents): line = line.replace(sent, f"") diff --git a/indextts/utils/front.py b/indextts/utils/front.py index d18034d..3f6816e 100644 --- a/indextts/utils/front.py +++ b/indextts/utils/front.py @@ -1,4 +1,5 @@ # -*- coding: utf-8 -*- +from functools import lru_cache import os import traceback import re @@ -9,7 +10,7 @@ from sentencepiece import SentencePieceProcessor class TextNormalizer: - def __init__(self): + def __init__(self, enable_glossary=False): self.zh_normalizer = None self.en_normalizer = None self.char_rep_map = { @@ -53,6 +54,18 @@ class TextNormalizer: "$": ".", **self.char_rep_map, } + self.enable_glossary = enable_glossary + # 术语词汇表：用户可自定义专业术语的读法 + # 格式: {"原始术语": {"en": "英文读法", "zh": "中文读法"}} + self.term_glossary = { + # "M.2": {"en": "M dot two", "zh": "M 二"}, + # "PCIe 5.0": {"en": "PCIE five", "zh": "PCIE 五点零"}, + # "PCIe 4.0": {"en": "PCIE four", "zh": "PCIE 四点零"}, + # "AHCI": "A H C I", + # "TTS": "T T S", + # "Inc.": {"en": "Ink"}, + # ".md": {"en": "dot M D", "zh": "点 M D"}, + } def match_email(self, email): # 正则表达式匹配邮箱格式：数字英文@数字英文.英文 @@ -124,6 +137,9 @@ class TextNormalizer: return "" if self.use_chinese(text): text = re.sub(TextNormalizer.ENGLISH_CONTRACTION_PATTERN, r"\1 is", text, flags=re.IGNORECASE) + # 应用术语词汇表（优先级最高，在所有保护之前） + if self.enable_glossary: + text = self.apply_glossary_terms(text, lang="zh") # 保护技术术语（如 GPT-5-nano）避免被中文normalizer错误处理 replaced_text, tech_list = self.save_tech_terms(text.rstrip()) replaced_text, pinyin_list = self.save_pinyin_tones(replaced_text) @@ -145,6 +161,9 @@ class TextNormalizer: else: try: text = re.sub(TextNormalizer.ENGLISH_CONTRACTION_PATTERN, r"\1 is", text, flags=re.IGNORECASE) + # 应用术语词汇表（优先级最高，在所有保护之前） + if self.enable_glossary: + text = self.apply_glossary_terms(text, lang="en") # 保护技术术语（如 GPT-5-Nano）避免被英文normalizer错误处理 replaced_text, tech_list = self.save_tech_terms(text) result = self.en_normalizer.normalize(replaced_text) @@ -242,6 +261,95 @@ class TextNormalizer: transformed_text = re.sub(r'\s*\s*', '-', normalized_text) return transformed_text + def apply_glossary_terms(self, text, lang="zh"): + """ + 应用术语词汇表，将专业术语替换为对应语言的读法 + + Args: + text: 待处理文本 + lang: 语言类型 "zh" 或 "en" + + Returns: + 处理后的文本 + + Example: + "M.2 NVMe SSD" -> (zh) "M 二 NVMe SSD" + "M.2 NVMe SSD" -> (en) "M dot two NVMe SSD" + """ + if not self.term_glossary: + return text + + # 按术语长度降序排列，避免短术语先匹配导致长术语无法匹配 + # 例如："PCIe 5.0" 应该在 "PCIe" 之前匹配 + sorted_terms = sorted(self.term_glossary.keys(), key=len, reverse=True) + @lru_cache(maxsize=42) + def get_term_pattern(term: str): + return re.compile(re.escape(term), re.IGNORECASE) + transformed_text = text + for term in sorted_terms: + term_value = self.term_glossary[term] + if isinstance(term_value, dict): + replacement = term_value.get(lang, term_value.get(lang, term)) + else: + replacement = term_value + # 使用正则进行大小写不敏感的替换 + pattern = get_term_pattern(term) + transformed_text = pattern.sub(replacement, transformed_text) + + return transformed_text + + def load_glossary(self, glossary_dict): + """ + 加载外部术语词汇表 + + Args: + glossary_dict: 术语词典，格式为 {"术语": {"en": "英文读法", "zh": "中文读法"}} + + Example: + normalizer.load_glossary({ + "M.2": {"en": "M dot two", "zh": "M 二"}, + "PCIe": {"en": "PCIE", "zh": "PCIE"} + }) + """ + if glossary_dict and isinstance(glossary_dict, dict): + self.term_glossary.update(glossary_dict) + + def load_glossary_from_yaml(self, glossary_path): + """ + 从 YAML 文件加载术语词汇表 + + Args: + glossary_path: YAML 文件路径 + + Example: + normalizer.load_glossary_from_yaml("checkpoints/glossary.yaml") + + YAML 文件格式: + M.2: + en: M dot two + zh: M 二 + NVMe: N-V-M-E # 中英文相同读法 + """ + if glossary_path and os.path.exists(glossary_path): + import yaml + with open(glossary_path, 'r', encoding='utf-8') as f: + external_glossary = yaml.safe_load(f) + if external_glossary and isinstance(external_glossary, dict): + self.term_glossary.update(external_glossary) + return True + return False + + def save_glossary_to_yaml(self, glossary_path): + """ + 保存术语词汇表到 YAML 文件 + + Args: + glossary_path: YAML 文件路径 + """ + import yaml + with open(glossary_path, 'w', encoding='utf-8') as f: + yaml.dump(self.term_glossary, f, allow_unicode=True, default_flow_style=False) + def save_pinyin_tones(self, original_text): """ 替换拼音声调为占位符 , , ... @@ -493,7 +601,7 @@ class TextTokenizer: if __name__ == "__main__": # 测试程序 - text_normalizer = TextNormalizer() + text_normalizer = TextNormalizer(enable_glossary=True) cases = [ "IndexTTS 正式发布1.0版本了，效果666", @@ -535,9 +643,11 @@ if __name__ == "__main__": "今天是个好日子 it's a good day", # 今天是个好日子 it is a good day # 术语 "such as XTTS, CosyVoice2, Fish-Speech, and F5-TTS", # such as xtts,cosyvoice two,fish-speech,and f five-tts - "GPT-5-Nano is the smallest and fastest variant in the GPT-5 model family.", - "GPT-5-Nano 是 GPT-5 模型家族中最小且速度最快的变体", - "2025/09/08 IndexTTS-2 全球发布" + "GPT-5-Nano is the smallest and fastest variant in the GPT-5 model family.", # GPT-five-Nano is the smallest and fastest variant in the GPT-five model family + "GPT-5-Nano 是 GPT-5 模型家族中最小且速度最快的变体", # GPT-五-Nano 是 GPT-五 系统中最小且速度最快的变体 + "2025/09/08 IndexTTS-2 全球发布", # 二零二五年九月八日 IndexTTS-二全球发布 + "Here are some highly-rated M.2 NVMe SSDs: Samsung 9100 PRO PCIe 5.0 SSD M.2, $139.99", # Here are some highly-rated M dot two NVMe SSD's, Samsung nine thousand one hundred PRO PCIE five SSD M dot two . one hundred and thirty nine dollars and ninety nine cents + "we dive deep into the showdown between DisplayPort 1.4 and HDMI 2.1 to determine which is the best choice for gaming enthusiasts", # 人名 "约瑟夫·高登-莱维特（Joseph Gordon-Levitt is an American actor）", "蒂莫西·唐纳德·库克（英文名：Timothy Donald Cook），通称蒂姆·库克（Tim Cook），美国商业经理、工业工程师和工业开发商，现任苹果公司首席执行官。", diff --git a/tools/i18n/locale/en_US.json b/tools/i18n/locale/en_US.json index e072dc1..031499f 100644 --- a/tools/i18n/locale/en_US.json +++ b/tools/i18n/locale/en_US.json @@ -46,5 +46,16 @@ "与音色参考音频相同": "Same as the voice reference", "情感随机采样": "Randomize emotion sampling", "显示实验功能": "Show experimental features", - "提示：此功能为实验版，结果尚不稳定，我们正在持续优化中。": "Note: This feature is currently experimental and may not produce satisfactory results. We're dedicated to improving its performance in a future release." + "提示：此功能为实验版，结果尚不稳定，我们正在持续优化中。": "Note: This feature is currently experimental and may not produce satisfactory results. We're dedicated to improving its performance in a future release.", + "自定义个别专业术语的读音": "Customize the pronunciation of each term or how it is \"say as\".", + "请至少输入一种读法": "Please enter at least one pronunciation", + "已添加": "Added", + "开启术语词汇读音": "Enable custom term pronunciations", + "添加术语": "Add term", + "暂无术语": "No custom terms added yet", + "请输入术语": "Please input the term", + "术语": "Term", + "已删除": "Deleted", + "英文读法": "English pronunciation", + "自定义术语词汇读音": "Customize term pronunciations" } \ No newline at end of file diff --git a/webui.py b/webui.py index 9c674a0..1cacf34 100644 --- a/webui.py +++ b/webui.py @@ -109,6 +109,21 @@ def get_example_cases(include_experimental = False): # exclude emotion control mode 3 (emotion from text description) return [x for x in example_cases if x[1] != EMO_CHOICES_ALL[3]] +def format_glossary_markdown(): + """将词汇表转换为Markdown表格格式""" + if not tts.normalizer.term_glossary: + return i18n("暂无术语") + + lines = [f"| {i18n('术语')} | {i18n('中文读法')} | {i18n('英文读法')} |"] + lines.append("|---|---|---|") + + for term, reading in tts.normalizer.term_glossary.items(): + zh = reading.get("zh", "") if isinstance(reading, dict) else reading + en = reading.get("en", "") if isinstance(reading, dict) else reading + lines.append(f"| {term} | {zh} | {en} |") + + return "\n".join(lines) + def gen_single(emo_control_method,prompt, text, emo_ref_path, emo_weight, vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8, @@ -195,8 +210,9 @@ with gr.Blocks(title="IndexTTS Demo") as demo: gen_button = gr.Button(i18n("生成语音"), key="gen_button",interactive=True) output_audio = gr.Audio(label=i18n("生成结果"), visible=True,key="output_audio") + with gr.Row(): experimental_checkbox = gr.Checkbox(label=i18n("显示实验功能"), value=False) - + glossary_checkbox = gr.Checkbox(label=i18n("开启术语词汇读音"), value=tts.normalizer.enable_glossary) with gr.Accordion(i18n("功能设置")): # 情感控制选项部分 with gr.Row(): @@ -246,6 +262,29 @@ with gr.Blocks(title="IndexTTS Demo") as demo: with gr.Row(visible=False) as emo_weight_group: emo_weight = gr.Slider(label=i18n("情感权重"), minimum=0.0, maximum=1.0, value=0.65, step=0.01) + # 术语词汇表管理 + with gr.Accordion(i18n("自定义术语词汇读音"), open=False, visible=tts.normalizer.enable_glossary) as glossary_accordion: + gr.Markdown(i18n("自定义个别专业术语的读音")) + with gr.Row(): + with gr.Column(scale=1): + glossary_term = gr.Textbox( + label=i18n("术语"), + placeholder="IndexTTS2", + ) + glossary_reading_zh = gr.Textbox( + label=i18n("中文读法"), + placeholder="Index T-T-S 二", + ) + glossary_reading_en = gr.Textbox( + label=i18n("英文读法"), + placeholder="Index T-T-S two", + ) + btn_add_term = gr.Button(i18n("添加术语"), scale=1) + with gr.Column(scale=2): + glossary_table = gr.Markdown( + value=format_glossary_markdown() + ) + with gr.Accordion(i18n("高级生成参数设置"), open=False, visible=True) as advanced_settings_group: with gr.Row(): with gr.Column(scale=1): @@ -353,6 +392,71 @@ with gr.Blocks(title="IndexTTS Demo") as demo: segments_preview: gr.update(value=df), } + # 术语词汇表事件处理函数 + def on_add_glossary_term(term, reading_zh, reading_en): + """添加术语到词汇表并自动保存""" + if not term: + return ( + gr.update(value=i18n("请输入术语")), + gr.update() + ) + if not reading_zh and not reading_en: + return ( + gr.update(value=i18n("请至少输入一种读法")), + gr.update() + ) + + # 构建读法数据 + if reading_zh and reading_en: + reading = {"zh": reading_zh, "en": reading_en} + elif reading_zh: + reading = {"zh": reading_zh} + elif reading_en: + reading = {"en": reading_en} + else: + reading = reading_zh or reading_en + + # 添加到词汇表 + tts.normalizer.term_glossary[term] = reading + + # 自动保存到文件 + tts.normalizer.save_glossary_to_yaml(tts.glossary_path) + + # 更新Markdown表格 + return ( + gr.update(value=f"{i18n('已添加')}: {term}"), + gr.update(value=format_glossary_markdown()) + ) + + def on_delete_glossary_term(table_data): + """删除选中的术语（通过清空输入框中的术语来触发）""" + # 注意：Gradio Dataframe 的选择功能有限，这里我们通过术语输入框来指定要删除的术语 + pass # 实际删除功能需要结合具体的选择机制 + + def on_delete_by_term(term): + """通过术语名称删除""" + if not term: + return ( + gr.update(value=i18n("请输入要删除的术语")), + gr.update() + ) + + if term in tts.normalizer.term_glossary: + del tts.normalizer.term_glossary[term] + # 自动保存 + tts.normalizer.save_glossary_to_yaml(tts.glossary_path) + + # 更新Markdown表格 + return ( + gr.update(value=f"{i18n('已删除')}: {term}"), + gr.update(value=format_glossary_markdown()) + ) + else: + return ( + gr.update(value=f"{i18n('术语不存在')}: {term}"), + gr.update() + ) + def on_method_change(emo_control_method): if emo_control_method == 1: # emotion reference audio return (gr.update(visible=True), @@ -410,6 +514,17 @@ with gr.Blocks(title="IndexTTS Demo") as demo: outputs=[emo_control_method, example_table] ) + def on_glossary_checkbox_change(is_enabled): + """控制术语词汇表的可见性""" + tts.normalizer.enable_glossary = is_enabled + return gr.update(visible=is_enabled) + + glossary_checkbox.change( + on_glossary_checkbox_change, + inputs=[glossary_checkbox], + outputs=[glossary_accordion] + ) + input_text_single.change( on_input_text_change, inputs=[input_text_single, max_text_tokens_per_segment], @@ -426,6 +541,14 @@ with gr.Blocks(title="IndexTTS Demo") as demo: inputs=[], outputs=[gen_button]) + # 术语词汇表事件绑定 + btn_add_term.click( + on_add_glossary_term, + inputs=[glossary_term, glossary_reading_zh, glossary_reading_en], + outputs=[glossary_table] + ) + + gen_button.click(gen_single, inputs=[emo_control_method,prompt_audio, input_text_single, emo_upload, emo_weight, vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8,