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Merge pull request #354 from Arcitec/indextts2-arc

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IndexTTS2 Maintenance Patches
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nanaoto 2025-09-18 13:58:23 +08:00 committed by GitHub
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7 changed files with 325 additions and 256 deletions
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8
examples/cases.jsonl
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@ -4,9 +4,9 @@
{"prompt_audio":"voice_04.wav","text":"你就需要我这种专业人士的帮助，就像手无缚鸡之力的人进入雪山狩猎，一定需要最老练的猎人指导。","emo_mode":0}
{"prompt_audio":"voice_05.wav","text":"在真正的日本剑道中，格斗过程极其短暂，常常短至半秒，最长也不超过两秒，利剑相击的转瞬间，已有一方倒在血泊中。但在这电光石火的对决之前，双方都要以一个石雕般凝固的姿势站定，长时间的逼视对方，这一过程可能长达十分钟！","emo_mode":0}
{"prompt_audio":"voice_06.wav","text":"今天呢，咱们开一部新书，叫《赛博朋克二零七七》。这词儿我听着都新鲜。这赛博朋克啊，简单理解就是“高科技，低生活”。这一听，我就明白了，于老师就爱用那高科技的东西，手机都得拿脚纹开，大冬天为了解锁脱得一丝不挂，冻得跟王八蛋似的。","emo_mode":0}
{"prompt_audio":"voice_07.wav","emo_audio":"emo_sad.wav","emo_weight": 1.0, "emo_mode":1,"text":"酒楼丧尽天良，开始借机竞拍房间，哎，一群蠢货。"}
{"prompt_audio":"voice_08.wav","emo_audio":"emo_hate.wav","emo_weight": 1.0, "emo_mode":1,"text":"你看看你，对我还有没有一点父子之间的信任了。"}
{"prompt_audio":"voice_09.wav","emo_vec_3":0.8,"emo_mode":2,"text":"对不起嘛！我的记性真的不太好，但是和你在一起的事情，我都会努力记住的~"}
{"prompt_audio":"voice_10.wav","emo_vec_7":1.0,"emo_mode":2,"text":"哇塞！这个爆率也太高了！欧皇附体了！"}
{"prompt_audio":"voice_07.wav","emo_audio":"emo_sad.wav","emo_weight":0.65,"emo_mode":1,"text":"酒楼丧尽天良，开始借机竞拍房间，哎，一群蠢货。"}
{"prompt_audio":"voice_08.wav","emo_audio":"emo_hate.wav","emo_weight":0.65,"emo_mode":1,"text":"你看看你，对我还有没有一点父子之间的信任了。"}
{"prompt_audio":"voice_09.wav","emo_weight": 0.8,"emo_mode":2,"emo_vec_3":0.8,"text":"对不起嘛！我的记性真的不太好，但是和你在一起的事情，我都会努力记住的~"}
{"prompt_audio":"voice_10.wav","emo_weight": 0.8,"emo_mode":2,"emo_vec_7":1.0,"text":"哇塞！这个爆率也太高了！欧皇附体了！"}
{"prompt_audio":"voice_11.wav","emo_mode":3,"emo_text":"极度悲伤","text":"这些年的时光终究是错付了... "}
{"prompt_audio":"voice_12.wav","emo_mode":3,"emo_text":"You scared me to death! What are you, a ghost?","text":"快躲起来！是他要来了！他要来抓我们了！"}

16
indextts/infer_v2.py
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@ -306,6 +306,22 @@ class IndexTTS2:
audio = audio[:, :max_audio_samples]
return audio, sr
def normalize_emo_vec(self, emo_vector, apply_bias=True):
# apply biased emotion factors for better user experience,
# by de-emphasizing emotions that can cause strange results
if apply_bias:
# [happy, angry, sad, afraid, disgusted, melancholic, surprised, calm]
emo_bias = [0.9375, 0.875, 1.0, 1.0, 0.9375, 0.9375, 0.6875, 0.5625]
emo_vector = [vec * bias for vec, bias in zip(emo_vector, emo_bias)]
# the total emotion sum must be 0.8 or less
emo_sum = sum(emo_vector)
if emo_sum > 0.8:
scale_factor = 0.8 / emo_sum
emo_vector = [vec * scale_factor for vec in emo_vector]
return emo_vector
# 原始推理模式
def infer(self, spk_audio_prompt, text, output_path,
emo_audio_prompt=None, emo_alpha=1.0,

2
pyproject.toml
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@ -65,7 +65,7 @@ dependencies = [
[project.optional-dependencies]
# To install the WebUI support, use `uv sync --extra webui` (or `--all-extras`).
webui = [
"gradio==5.44.1",
"gradio==5.45.0",
]
# To install the DeepSpeed support, use `uv sync --extra deepspeed` (or `--all-extras`).
deepspeed = [

5
tools/i18n/locale/en_US.json
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@ -42,8 +42,9 @@
"请上传情感参考音频": "Please upload the emotion reference audio",
"当前模型版本": "Current model version: ",
"请输入目标文本": "Please input the text to synthesize",
"例如：委屈巴巴、危险在悄悄逼近": "e.g. deeply sad, danger is creeping closer",
"例如：委屈巴巴、危险在悄悄逼近": "e.g. \"deeply sad\", \"danger is creeping closer\"",
"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"
"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."
}

5
tools/i18n/locale/zh_CN.json
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@ -39,6 +39,9 @@
"参数会影响音频多样性和生成速度详见": "参数会影响音频多样性和生成速度详见",
"是否进行采样": "是否进行采样",
"生成Token最大数量，过小导致音频被截断": "生成Token最大数量，过小导致音频被截断",
"例如：委屈巴巴、危险在悄悄逼近": "例如：委屈巴巴、危险在悄悄逼近",
"与音色参考音频相同": "与音色参考音频相同",
"情感随机采样": "情感随机采样",
"显示实验功能": "显示实验功能",
"例如：委屈巴巴、危险在悄悄逼近": "例如：委屈巴巴、危险在悄悄逼近"
"提示：此功能为实验版，结果尚不稳定，我们正在持续优化中。": "提示：此功能为实验版，结果尚不稳定，我们正在持续优化中。"
}

379
uv.lock generated
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150
webui.py
View File

@ -1,3 +1,4 @@
import html
import json
import os
import sys
@ -6,8 +7,6 @@ import time
import warnings
import numpy as np
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.filterwarnings("ignore", category=UserWarning)
@ -65,19 +64,18 @@ LANGUAGES = {
"中文": "zh_CN",
"English": "en_US"
}
EMO_CHOICES = [i18n("与音色参考音频相同"),
EMO_CHOICES_ALL = [i18n("与音色参考音频相同"),
i18n("使用情感参考音频"),
i18n("使用情感向量控制"),
i18n("使用情感描述文本控制")]
EMO_CHOICES_BASE = EMO_CHOICES[:3] # 基础选项
EMO_CHOICES_EXPERIMENTAL = EMO_CHOICES # 全部选项（包括文本描述）
EMO_CHOICES_OFFICIAL = EMO_CHOICES_ALL[:-1] # skip experimental features
os.makedirs("outputs/tasks",exist_ok=True)
os.makedirs("prompts",exist_ok=True)
MAX_LENGTH_TO_USE_SPEED = 70
example_cases = []
with open("examples/cases.jsonl", "r", encoding="utf-8") as f:
example_cases = []
for line in f:
line = line.strip()
if not line:
@ -87,8 +85,9 @@ with open("examples/cases.jsonl", "r", encoding="utf-8") as f:
emo_audio_path = os.path.join("examples",example["emo_audio"])
else:
emo_audio_path = None
example_cases.append([os.path.join("examples", example.get("prompt_audio", "sample_prompt.wav")),
EMO_CHOICES[example.get("emo_mode",0)],
EMO_CHOICES_ALL[example.get("emo_mode",0)],
example.get("text"),
emo_audio_path,
example.get("emo_weight",1.0),
@ -101,16 +100,14 @@ with open("examples/cases.jsonl", "r", encoding="utf-8") as f:
example.get("emo_vec_6",0),
example.get("emo_vec_7",0),
example.get("emo_vec_8",0),
example.get("emo_text") is not None]
)
])
def normalize_emo_vec(emo_vec):
# emotion factors for better user experience
k_vec = [0.75,0.70,0.80,0.80,0.75,0.75,0.55,0.45]
tmp = np.array(k_vec) * np.array(emo_vec)
if np.sum(tmp) > 0.8:
tmp = tmp * 0.8/ np.sum(tmp)
return tmp.tolist()
def get_example_cases(include_experimental = False):
if include_experimental:
return example_cases # show every example
# exclude emotion control mode 3 (emotion from text description)
return [x for x in example_cases if x[1] != EMO_CHOICES_ALL[3]]
def gen_single(emo_control_method,prompt, text,
emo_ref_path, emo_weight,
@ -142,12 +139,10 @@ def gen_single(emo_control_method,prompt, text,
if emo_control_method == 0: # emotion from speaker
emo_ref_path = None # remove external reference audio
if emo_control_method == 1: # emotion from reference audio
# normalize emo_alpha for better user experience
emo_weight = emo_weight * 0.8
pass
if emo_control_method == 2: # emotion from custom vectors
vec = [vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8]
vec = normalize_emo_vec(vec)
vec = tts.normalize_emo_vec(vec, apply_bias=True)
else:
# don't use the emotion vector inputs for the other modes
vec = None
@ -171,6 +166,12 @@ def update_prompt_audio():
update_button = gr.update(interactive=True)
return update_button
def create_warning_message(warning_text):
return gr.HTML(f"<div style=\"padding: 0.5em 0.8em; border-radius: 0.5em; background: #ffa87d; color: #000; font-weight: bold\">{html.escape(warning_text)}</div>")
def create_experimental_warning_message():
return create_warning_message(i18n('提示：此功能为实验版，结果尚不稳定，我们正在持续优化中。'))
with gr.Blocks(title="IndexTTS Demo") as demo:
mutex = threading.Lock()
gr.HTML('''
@ -193,14 +194,24 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
input_text_single = gr.TextArea(label=i18n("文本"),key="input_text_single", placeholder=i18n("请输入目标文本"), info=f"{i18n('当前模型版本')}{tts.model_version or '1.0'}")
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")
experimental_checkbox = gr.Checkbox(label=i18n("显示实验功能"),value=False)
experimental_checkbox = gr.Checkbox(label=i18n("显示实验功能"), value=False)
with gr.Accordion(i18n("功能设置")):
# 情感控制选项部分
with gr.Row():
emo_control_method = gr.Radio(
choices=EMO_CHOICES_BASE,
choices=EMO_CHOICES_OFFICIAL,
type="index",
value=EMO_CHOICES_BASE[0],label=i18n("情感控制方式"))
value=EMO_CHOICES_OFFICIAL[0],label=i18n("情感控制方式"))
# we MUST have an extra, INVISIBLE list of *all* emotion control
# methods so that gr.Dataset() can fetch ALL control mode labels!
# otherwise, the gr.Dataset()'s experimental labels would be empty!
emo_control_method_all = gr.Radio(
choices=EMO_CHOICES_ALL,
type="index",
value=EMO_CHOICES_ALL[0], label=i18n("情感控制方式"),
visible=False) # do not render
# 情感参考音频部分
with gr.Group(visible=False) as emotion_reference_group:
with gr.Row():
@ -225,17 +236,17 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
vec8 = gr.Slider(label=i18n("平静"), minimum=0.0, maximum=1.0, value=0.0, step=0.05)
with gr.Group(visible=False) as emo_text_group:
create_experimental_warning_message()
with gr.Row():
emo_text = gr.Textbox(label=i18n("情感描述文本"),
placeholder=i18n("请输入情绪描述（或留空以自动使用目标文本作为情绪描述）"),
value="",
info=i18n("例如：委屈巴巴、危险在悄悄逼近"))
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=0.8, step=0.01)
emo_weight = gr.Slider(label=i18n("情感权重"), minimum=0.0, maximum=1.0, value=0.65, step=0.01)
with gr.Accordion(i18n("高级生成参数设置"), open=False,visible=False) as advanced_settings_group:
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):
gr.Markdown(f"**{i18n('GPT2 采样设置')}** _{i18n('参数会影响音频多样性和生成速度详见')} [Generation strategies](https://huggingface.co/docs/transformers/main/en/generation_strategies)._")
@ -273,29 +284,54 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
# typical_sampling, typical_mass,
]
if len(example_cases) > 2:
example_table = gr.Examples(
examples=example_cases[:-2],
examples_per_page=20,
inputs=[prompt_audio,
emo_control_method,
# we must use `gr.Dataset` to support dynamic UI rewrites, since `gr.Examples`
# binds tightly to UI and always restores the initial state of all components,
# such as the list of available choices in emo_control_method.
example_table = gr.Dataset(label="Examples",
samples_per_page=20,
samples=get_example_cases(include_experimental=False),
type="values",
# these components are NOT "connected". it just reads the column labels/available
# states from them, so we MUST link to the "all options" versions of all components,
# such as `emo_control_method_all` (to be able to see EXPERIMENTAL text labels)!
components=[prompt_audio,
emo_control_method_all, # important: support all mode labels!
input_text_single,
emo_upload,
emo_weight,
emo_text,
vec1,vec2,vec3,vec4,vec5,vec6,vec7,vec8,experimental_checkbox]
vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8]
)
elif len(example_cases) > 0:
example_table = gr.Examples(
examples=example_cases,
examples_per_page=20,
inputs=[prompt_audio,
def on_example_click(example):
print(f"Example clicked: ({len(example)} values) = {example!r}")
return (
gr.update(value=example[0]),
gr.update(value=example[1]),
gr.update(value=example[2]),
gr.update(value=example[3]),
gr.update(value=example[4]),
gr.update(value=example[5]),
gr.update(value=example[6]),
gr.update(value=example[7]),
gr.update(value=example[8]),
gr.update(value=example[9]),
gr.update(value=example[10]),
gr.update(value=example[11]),
gr.update(value=example[12]),
gr.update(value=example[13]),
)
# click() event works on both desktop and mobile UI
example_table.click(on_example_click,
inputs=[example_table],
outputs=[prompt_audio,
emo_control_method,
input_text_single,
emo_upload,
emo_weight,
emo_text,
vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8, experimental_checkbox]
vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8]
)
def on_input_text_change(text, max_text_tokens_per_segment):
@ -317,7 +353,7 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
segments_preview: gr.update(value=df),
}
def on_method_select(emo_control_method):
def on_method_change(emo_control_method):
if emo_control_method == 1: # emotion reference audio
return (gr.update(visible=True),
gr.update(visible=False),
@ -330,7 +366,7 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
gr.update(visible=True),
gr.update(visible=True),
gr.update(visible=False),
gr.update(visible=False)
gr.update(visible=True)
)
elif emo_control_method == 3: # emotion text description
return (gr.update(visible=False),
@ -347,15 +383,7 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
gr.update(visible=False)
)
def on_experimental_change(is_exp):
# 切换情感控制选项
# 第三个返回值实际没有起作用
if is_exp:
return gr.update(choices=EMO_CHOICES_EXPERIMENTAL, value=EMO_CHOICES_EXPERIMENTAL[0]), gr.update(visible=True),gr.update(value=example_cases)
else:
return gr.update(choices=EMO_CHOICES_BASE, value=EMO_CHOICES_BASE[0]), gr.update(visible=False),gr.update(value=example_cases[:-2])
emo_control_method.select(on_method_select,
emo_control_method.change(on_method_change,
inputs=[emo_control_method],
outputs=[emotion_reference_group,
emotion_randomize_group,
@ -364,16 +392,28 @@ with gr.Blocks(title="IndexTTS Demo") as demo:
emo_weight_group]
)
input_text_single.change(
on_input_text_change,
inputs=[input_text_single, max_text_tokens_per_segment],
outputs=[segments_preview]
def on_experimental_change(is_experimental, current_mode_index):
# 切换情感控制选项
new_choices = EMO_CHOICES_ALL if is_experimental else EMO_CHOICES_OFFICIAL
# if their current mode selection doesn't exist in new choices, reset to 0.
# we don't verify that OLD index means the same in NEW list, since we KNOW it does.
new_index = current_mode_index if current_mode_index < len(new_choices) else 0
return (
gr.update(choices=new_choices, value=new_choices[new_index]),
gr.update(samples=get_example_cases(include_experimental=is_experimental)),
)
experimental_checkbox.change(
on_experimental_change,
inputs=[experimental_checkbox],
outputs=[emo_control_method, advanced_settings_group,example_table.dataset] # 高级参数Accordion
inputs=[experimental_checkbox, emo_control_method],
outputs=[emo_control_method, example_table]
)
input_text_single.change(
on_input_text_change,
inputs=[input_text_single, max_text_tokens_per_segment],
outputs=[segments_preview]
)
max_text_tokens_per_segment.change(