Spaces:
Sleeping
Sleeping
File size: 25,973 Bytes
c5ed230 5854014 c5ed230 5854014 c5ed230 3b8fb9b c5ed230 5854014 c5ed230 3b8fb9b d94ccbe 5854014 3b8fb9b c5ed230 5854014 c5ed230 5854014 c5ed230 5854014 c5ed230 d94ccbe 5854014 c5ed230 d94ccbe c5ed230 d94ccbe c5ed230 d94ccbe c5ed230 d94ccbe c5ed230 d94ccbe 5854014 c5ed230 d94ccbe c5ed230 d94ccbe c5ed230 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 |
<div class="title" align=center>
<h1>vits-simple-api</h1>
<div>Simply call the vits api</div>
<br/>
<br/>
<p>
<img src="https://img.shields.io/github/license/Artrajz/vits-simple-api">
<img src="https://img.shields.io/badge/python-3.9%7C3.10-green">
<a href="https://hub.docker.com/r/artrajz/vits-simple-api">
<img src="https://img.shields.io/docker/pulls/artrajz/vits-simple-api"></a>
</p>
<a href="https://github.com/Artrajz/vits-simple-api/blob/main/README.md">English</a>|<a href="https://github.com/Artrajz/vits-simple-api/blob/main/README_zh.md">中文文档</a>
<br/>
</div>
# Feature
- [x] VITS语音合成
- [x] VITS语音转换
- [x] HuBert-soft VITS模型
- [x] W2V2 VITS / emotional-vits维度情感模型
- [x] 加载多模型
- [x] 自动识别语言并处理,根据模型的cleaner设置语言类型识别的范围,支持自定义语言类型范围
- [x] 自定义默认参数
- [x] 长文本批处理
- [x] GPU加速推理
- [x] SSML语音合成标记语言(完善中...)
<details><summary>Update Logs</summary><pre><code>
<h2>2023.6.5</h2>
<p>更换音频编码使用的库,增加flac格式,增加中文对读简单数学公式的支持</p>
<h2>2023.5.24</h2>
<p>添加dimensional_emotion api,从文件夹加载多个npy文件,Docker添加了Linux/ARM64和Linux/ARM64/v8平台</p>
<h2>2023.5.15</h2>
<p>增加english_cleaner,需要额外安装espeak才能使用</p>
<h2>2023.5.12</h2>
<p>增加ssml支持,但仍需完善。重构部分功能,hubert_vits中的speaker_id改为id</p>
<h2>2023.5.2</h2>
<p>增加w2v2-vits/emotional-vits模型支持,修改了speakers映射表并添加了对应模型支持的语言</p>
<h2>2023.4.23</h2>
<p>增加api key鉴权,默认禁用,需要在config.py中启用</p>
<h2>2023.4.17</h2>
<p>修改单语言的cleaner需要标注才会clean,增加GPU加速推理,但需要手动安装gpu推理环境</p>
<h2>2023.4.12</h2>
<p>项目由MoeGoe-Simple-API更名为vits-simple-api,支持长文本批处理,增加长文本分段阈值max</p>
<h2>2023.4.7</h2>
<p>增加配置文件可自定义默认参数,本次更新需要手动更新config.py,具体使用方法见config.py</p>
<h2>2023.4.6</h2>
<p>加入自动识别语种选项auto,lang参数默认修改为auto,自动识别仍有一定缺陷,请自行选择</p>
<p>统一POST请求类型为multipart/form-data</p>
</code></pre></details>
## demo
[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/Artrajz/vits-simple-api)
注意不同的id支持的语言可能有所不同。[speakers](https://artrajz-vits-simple-api.hf.space/voice/speakers)
- `https://artrajz-vits-simple-api.hf.space/voice/vits?text=你好,こんにちは&id=164`
- `https://artrajz-vits-simple-api.hf.space/voice/vits?text=我觉得1%2B1≠3&id=164&lang=zh`(get中一些字符需要转义不然会被过滤掉)
- `https://artrajz-vits-simple-api.hf.space/voice/vits?text=Difficult the first time, easy the second.&id=4`
- 激动:`https://artrajz-vits-simple-api.hf.space/voice/w2v2-vits?text=こんにちは&id=3&emotion=111`
- 小声:`https://artrajz-vits-simple-api.hf.space/voice/w2v2-vits?text=こんにちは&id=3&emotion=2077`
https://user-images.githubusercontent.com/73542220/237995061-c1f25b4e-dd86-438a-9363-4bb1fe65b425.mov
# 部署
## Docker部署
### 镜像拉取脚本
```
bash -c "$(wget -O- https://raw.githubusercontent.com/Artrajz/vits-simple-api/main/vits-simple-api-installer-latest.sh)"
```
- 目前docker镜像支持的平台`linux/amd64,linux/arm64`
- 在拉取完成后,需要导入VITS模型才能使用,请根据以下步骤导入模型。
### 下载VITS模型
将模型放入`/usr/local/vits-simple-api/Model`
<details><summary>Folder structure</summary><pre><code>
│ hubert-soft-0d54a1f4.pt
│ model.onnx
│ model.yaml
├─g
│ config.json
│ G_953000.pth
│
├─louise
│ 360_epochs.pth
│ config.json
│
├─Nene_Nanami_Rong_Tang
│ 1374_epochs.pth
│ config.json
│
├─Zero_no_tsukaima
│ 1158_epochs.pth
│ config.json
│
└─npy
25ecb3f6-f968-11ed-b094-e0d4e84af078.npy
all_emotions.npy
</code></pre></details>
### 修改模型路径
Modify in `/usr/local/vits-simple-api/config.py`
<details><summary>config.py</summary><pre><code>
# 在此填写模型路径
MODEL_LIST = [
# VITS
[ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/1374_epochs.pth", ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/config.json"],
[ABS_PATH + "/Model/Zero_no_tsukaima/1158_epochs.pth", ABS_PATH + "/Model/Zero_no_tsukaima/config.json"],
[ABS_PATH + "/Model/g/G_953000.pth", ABS_PATH + "/Model/g/config.json"],
# HuBert-VITS (Need to configure HUBERT_SOFT_MODEL)
[ABS_PATH + "/Model/louise/360_epochs.pth", ABS_PATH + "/Model/louise/config.json"],
# W2V2-VITS (Need to configure DIMENSIONAL_EMOTION_NPY)
[ABS_PATH + "/Model/w2v2-vits/1026_epochs.pth", ABS_PATH + "/Model/w2v2-vits/config.json"],
]
# hubert-vits: hubert soft 编码器
HUBERT_SOFT_MODEL = ABS_PATH + "/Model/hubert-soft-0d54a1f4.pt"
# w2v2-vits: Dimensional emotion npy file
# 加载单独的npy: ABS_PATH+"/all_emotions.npy
# 加载多个npy: [ABS_PATH + "/emotions1.npy", ABS_PATH + "/emotions2.npy"]
# 从文件夹里加载npy: ABS_PATH + "/Model/npy"
DIMENSIONAL_EMOTION_NPY = ABS_PATH + "/Model/npy"
# w2v2-vits: 需要在同一路径下有model.onnx和model.yaml
DIMENSIONAL_EMOTION_MODEL = ABS_PATH + "/Model/model.yaml"
</code></pre></details>
### 启动
`docker compose up -d`
或者重新执行拉取脚本
### 镜像更新
重新执行docker镜像拉取脚本即可
## 虚拟环境部署
### Clone
`git clone https://github.com/Artrajz/vits-simple-api.git`
### 下载python依赖
推荐使用python的虚拟环境,python版本 >= 3.9
`pip install -r requirements.txt`
windows下可能安装不了fasttext,可以用以下命令安装,附[wheels下载地址](https://www.lfd.uci.edu/~gohlke/pythonlibs/#fasttext)
```
#python3.10 win_amd64
pip install https://github.com/Artrajz/archived/raw/main/fasttext/fasttext-0.9.2-cp310-cp310-win_amd64.whl
#python3.9 win_amd64
pip install https://github.com/Artrajz/archived/raw/main/fasttext/fasttext-0.9.2-cp39-cp39-win_amd64.whl
```
### 下载VITS模型
将模型放入 `/path/to/vits-simple-api/Model`
<details><summary>文件夹结构</summary><pre><code>
├─g
│ config.json
│ G_953000.pth
│
├─louise
│ 360_epochs.pth
│ config.json
│ hubert-soft-0d54a1f4.pt
│
├─Nene_Nanami_Rong_Tang
│ 1374_epochs.pth
│ config.json
│
└─Zero_no_tsukaima
1158_epochs.pth
config.json
</code></pre></details>
### 修改模型路径
在 `/path/to/vits-simple-api/config.py` 修改
<details><summary>config.py</summary><pre><code>
# 在此填写模型路径
MODEL_LIST = [
# VITS
[ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/1374_epochs.pth", ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/config.json"],
[ABS_PATH + "/Model/Zero_no_tsukaima/1158_epochs.pth", ABS_PATH + "/Model/Zero_no_tsukaima/config.json"],
[ABS_PATH + "/Model/g/G_953000.pth", ABS_PATH + "/Model/g/config.json"],
# HuBert-VITS (Need to configure HUBERT_SOFT_MODEL)
[ABS_PATH + "/Model/louise/360_epochs.pth", ABS_PATH + "/Model/louise/config.json"],
# W2V2-VITS (Need to configure DIMENSIONAL_EMOTION_NPY)
[ABS_PATH + "/Model/w2v2-vits/1026_epochs.pth", ABS_PATH + "/Model/w2v2-vits/config.json"],
]
# hubert-vits: hubert soft 编码器
HUBERT_SOFT_MODEL = ABS_PATH + "/Model/hubert-soft-0d54a1f4.pt"
# w2v2-vits: Dimensional emotion npy file
# 加载单独的npy: ABS_PATH+"/all_emotions.npy
# 加载多个npy: [ABS_PATH + "/emotions1.npy", ABS_PATH + "/emotions2.npy"]
# 从文件夹里加载npy: ABS_PATH + "/Model/npy"
DIMENSIONAL_EMOTION_NPY = ABS_PATH + "/Model/npy"
# w2v2-vits: 需要在同一路径下有model.onnx和model.yaml
DIMENSIONAL_EMOTION_MODEL = ABS_PATH + "/Model/model.yaml"
</code></pre></details>
### 启动
`python app.py`
# GPU 加速
## windows
### 安装CUDA
查看显卡最高支持CUDA的版本
```
nvidia-smi
```
以CUDA11.7为例,[官网](https://developer.nvidia.com/cuda-11-7-0-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exe_local)
### 安装GPU版pytorch
CUDA11.7对应的pytorch是用这个命令安装
```
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
```
对应版本的命令可以在[官网](https://pytorch.org/get-started/locally/)找到
## Linux
安装过程类似,但我没有相应的环境所以没办法测试
# Openjtalk安装问题
如果你是arm64架构的平台,由于pypi官网上没有arm64对应的whl,可能安装会出现一些问题,你可以使用我构建的whl来安装
```
pip install openjtalk==0.3.0.dev2 --index-url https://pypi.artrajz.cn/simple
```
或者是自己手动构建一个whl,可以根据[教程](https://artrajz.cn/index.php/archives/167/)来构建
# API
## GET
#### speakers list
- GET http://127.0.0.1:23456/voice/speakers
返回id对应角色的映射表
#### voice vits
- GET http://127.0.0.1:23456/voice/vits?text=text
其他参数不指定时均为默认值
- GET http://127.0.0.1:23456/voice/vits?text=[ZH]text[ZH][JA]text[JA]&lang=mix
lang=mix时文本要标注
- GET http://127.0.0.1:23456/voice/vits?text=text&id=142&format=wav&lang=zh&length=1.4
文本为text,角色id为142,音频格式为wav,文本语言为zh,语音长度为1.4,其余参数默认
#### check
- GET http://127.0.0.1:23456/voice/check?id=0&model=vits
## POST
- python
```python
import re
import requests
import os
import random
import string
from requests_toolbelt.multipart.encoder import MultipartEncoder
abs_path = os.path.dirname(__file__)
base = "http://127.0.0.1:23456"
# 映射表
def voice_speakers():
url = f"{base}/voice/speakers"
res = requests.post(url=url)
json = res.json()
for i in json:
print(i)
for j in json[i]:
print(j)
return json
# 语音合成 voice vits
def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, max=50):
fields = {
"text": text,
"id": str(id),
"format": format,
"lang": lang,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
"max": str(max)
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
# 语音转换 hubert-vits
def voice_hubert_vits(upload_path, id, format="wav", length=1, noise=0.667, noisew=0.8):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg
with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
"id": str(id),
"format": format,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/hubert-vits"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
# 维度情感模型 w2v2-vits
def voice_w2v2_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, max=50, emotion=0):
fields = {
"text": text,
"id": str(id),
"format": format,
"lang": lang,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
"max": str(max),
"emotion": str(emotion)
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/w2v2-vits"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
# 语音转换 同VITS模型内角色之间的音色转换
def voice_conversion(upload_path, original_id, target_id):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg
with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
"original_id": str(original_id),
"target_id": str(target_id),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/conversion"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
def voice_ssml(ssml):
fields = {
"ssml": ssml,
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/ssml"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
def voice_dimensional_emotion(upload_path):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg
with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/dimension-emotion"
res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"
with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
```
## API KEY
在config.py中设置`API_KEY_ENABLED = True`以启用,api key填写:`API_KEY = "api-key"`。
启用后,GET请求中使用需要增加参数api_key,POST请求中使用需要在header中添加参数`X-API-KEY`。
# Parameter
## VITS语音合成
| Name | Parameter | Is must | Default | Type | Instruction |
| ------------- | --------- | ------- | ------- | ----- | ------------------------------------------------------------ |
| 合成文本 | text | true | | str | 需要合成语音的文本。 |
| 角色id | id | false | 0 | int | 即说话人id。 |
| 音频格式 | format | false | wav | str | 支持wav,ogg,silk,mp3,flac |
| 文本语言 | lang | false | auto | str | auto为自动识别语言模式,也是默认模式。lang=mix时,文本应该用[ZH] 或 [JA] 包裹。方言无法自动识别。 |
| 语音长度/语速 | length | false | 1.0 | float | 调节语音长度,相当于调节语速,该数值越大语速越慢。 |
| 噪声 | noise | false | 0.33 | float | 样本噪声,控制合成的随机性。 |
| sdp噪声 | noisew | false | 0.4 | float | 随机时长预测器噪声,控制音素发音长度。 |
| 分段阈值 | max | false | 50 | int | 按标点符号分段,加起来大于max时为一段文本。max<=0表示不分段。 |
| 流式响应 | streaming | false | false | bool | 流式合成语音,更快的首包响应。 |
## VITS 语音转换
| Name | Parameter | Is must | Default | Type | Instruction |
| ---------- | ----------- | ------- | ------- | ---- | ---------------------- |
| 上传音频 | upload | true | | file | wav or ogg |
| 源角色id | original_id | true | | int | 上传文件所使用的角色id |
| 目标角色id | target_id | true | | int | 要转换的目标角色id |
## HuBert-VITS 语音转换
| Name | Parameter | Is must | Default | Type | Instruction |
| ------------- | --------- | ------- | ------- | ----- | ------------------------------------------------ |
| 上传音频 | upload | true | | file | 需要转换说话人的音频文件。 |
| 目标角色id | id | true | | int | 目标说话人id。 |
| 音频格式 | format | true | | str | wav,ogg,silk |
| 语音长度/语速 | length | true | | float | 调节语音长度,相当于调节语速,该数值越大语速越慢 |
| 噪声 | noise | true | | float | 样本噪声,控制合成的随机性。 |
| sdp噪声 | noisew | true | | float | 随机时长预测器噪声,控制音素发音长度。 |
## Dimensional emotion
| Name | Parameter | Is must | Default | Type | Instruction |
| -------- | --------- | ------- | ------- | ---- | ----------------------------- |
| 上传音频 | upload | true | | file | 返回存储维度情感向量的npy文件 |
## W2V2-VITS
| Name | Parameter | Is must | Default | Type | Instruction |
| ------------- | --------- | ------- | ------- | ----- | ------------------------------------------------------------ |
| 合成文本 | text | true | | str | 需要合成语音的文本。 |
| 角色id | id | false | 0 | int | 即说话人id。 |
| 音频格式 | format | false | wav | str | 支持wav,ogg,silk,mp3,flac |
| 文本语言 | lang | false | auto | str | auto为自动识别语言模式,也是默认模式。lang=mix时,文本应该用[ZH] 或 [JA] 包裹。方言无法自动识别。 |
| 语音长度/语速 | length | false | 1.0 | float | 调节语音长度,相当于调节语速,该数值越大语速越慢 |
| 噪声 | noise | false | 0.33 | float | 样本噪声,控制合成的随机性。 |
| sdp噪声 | noisew | false | 0.4 | float | 随机时长预测器噪声,控制音素发音长度。 |
| 分段阈值 | max | false | 50 | int | 按标点符号分段,加起来大于max时为一段文本。max<=0表示不分段。 |
| 维度情感 | emotion | false | 0 | int | 范围取决于npy情感参考文件,如[innnky](https://huggingface.co/spaces/innnky/nene-emotion/tree/main)的all_emotions.npy模型范围是0-5457 |
## SSML语音合成标记语言
目前支持的元素与属性
`speak`元素
| Attribute | Description | Is must |
| --------- | ------------------------------------------------------------ | ------- |
| id | 默认值从`config.py`中读取 | false |
| lang | 默认值从`config.py`中读取 | false |
| length | 默认值从`config.py`中读取 | false |
| noise | 默认值从`config.py`中读取 | false |
| noisew | 默认值从`config.py`中读取 | false |
| max | 按标点符号分段,加起来大于max时为一段文本。max<=0表示不分段,这里默认为0。 | false |
| model | 默认为vits,可选`w2v2-vits`,`emotion-vits` | false |
| emotion | 只有用`w2v2-vits`或`emotion-vits`时`emotion`才生效,范围取决于npy情感参考文件 | false |
`voice`元素
优先级大于`speak`
| Attribute | Description | Is must |
| --------- | ------------------------------------------------------------ | ------- |
| id | 默认值从`config.py`中读取 | false |
| lang | 默认值从`config.py`中读取 | false |
| length | 默认值从`config.py`中读取 | false |
| noise | 默认值从`config.py`中读取 | false |
| noisew | 默认值从`config.py`中读取 | false |
| max | 按标点符号分段,加起来大于max时为一段文本。max<=0表示不分段,这里默认为0。 | false |
| model | 默认为vits,可选`w2v2-vits`,`emotion-vits` | false |
| emotion | 只有用`w2v2-vits`或`emotion-vits`时`emotion`才会生效 | false |
`break`元素
| Attribute | Description | Is must |
| --------- | ------------------------------------------------------------ | ------- |
| strength | x-weak,weak,medium(默认值),strong,x-strong | false |
| time | 暂停的绝对持续时间,以秒为单位(例如 `2s`)或以毫秒为单位(例如 `500ms`)。 有效值的范围为 0 到 5000 毫秒。 如果设置的值大于支持的最大值,则服务将使用 `5000ms`。 如果设置了 `time` 属性,则会忽略 `strength` 属性。 | false |
| Strength | Relative Duration |
| :------- | :---------------- |
| x-weak | 250 毫秒 |
| weak | 500 毫秒 |
| Medium | 750 毫秒 |
| Strong | 1000 毫秒 |
| x-strong | 1250 毫秒 |
示例
```xml
<speak lang="zh" format="mp3" length="1.2">
<voice id="92" >这几天心里颇不宁静。</voice>
<voice id="125">今晚在院子里坐着乘凉,忽然想起日日走过的荷塘,在这满月的光里,总该另有一番样子吧。</voice>
<voice id="142">月亮渐渐地升高了,墙外马路上孩子们的欢笑,已经听不见了;</voice>
<voice id="98">妻在屋里拍着闰儿,迷迷糊糊地哼着眠歌。</voice>
<voice id="120">我悄悄地披了大衫,带上门出去。</voice><break time="2s"/>
<voice id="121">沿着荷塘,是一条曲折的小煤屑路。</voice>
<voice id="122">这是一条幽僻的路;白天也少人走,夜晚更加寂寞。</voice>
<voice id="123">荷塘四面,长着许多树,蓊蓊郁郁的。</voice>
<voice id="124">路的一旁,是些杨柳,和一些不知道名字的树。</voice>
<voice id="125">没有月光的晚上,这路上阴森森的,有些怕人。</voice>
<voice id="126">今晚却很好,虽然月光也还是淡淡的。</voice><break time="2s"/>
<voice id="127">路上只我一个人,背着手踱着。</voice>
<voice id="128">这一片天地好像是我的;我也像超出了平常的自己,到了另一个世界里。</voice>
<voice id="129">我爱热闹,也爱冷静;<break strength="x-weak"/>爱群居,也爱独处。</voice>
<voice id="130">像今晚上,一个人在这苍茫的月下,什么都可以想,什么都可以不想,便觉是个自由的人。</voice>
<voice id="131">白天里一定要做的事,一定要说的话,现在都可不理。</voice>
<voice id="132">这是独处的妙处,我且受用这无边的荷香月色好了。</voice>
</speak>
```
# 交流平台
现在只有 [Q群](https://qm.qq.com/cgi-bin/qm/qr?k=-1GknIe4uXrkmbDKBGKa1aAUteq40qs_&jump_from=webapi&authKey=x5YYt6Dggs1ZqWxvZqvj3fV8VUnxRyXm5S5Kzntc78+Nv3iXOIawplGip9LWuNR/)
# 鸣谢
- vits:https://github.com/jaywalnut310/vits
- MoeGoe:https://github.com/CjangCjengh/MoeGoe
- emotional-vits:https://github.com/innnky/emotional-vits
- vits-uma-genshin-honkai:https://huggingface.co/spaces/zomehwh/vits-uma-genshin-honkai
- vits_chinese:https://github.com/PlayVoice/vits_chinese
|