Bert-vits2-v2.2新版本本地训练推理整合包(原神八重神子英文模型miko)
近日，Bert-vits2-v2.2如约更新，该新版本v2.2主要把Emotion 模型换用CLAP多模态模型，推理支持输入text prompt提示词和audio prompt提示语音来进行引导风格化合成，让推理音色更具情感特色，并且推出了新的预处理webuI，操作上更加亲民和接地气。
更多情报请参见Bert-vits2官网：
https://github.com/fishaudio/Bert-VITS2/releases/tag/v2.2
与此同时，基于FastApi的推理web界面项目也同步适配了Bert-vits2-v2.2版本，官网如下：
https://github.com/jiangyuxiaoxiao/Bert-VITS2-UI
本次我们基于此两个项目来克隆原神角色八重神子的英文语音模型miko。
Bert-vits2-v2.2新的底模和情感模型
首先克隆Bert-vits2-v2.2官方项目：
git clone https://github.com/fishaudio/Bert-VITS2/tree/v2.2
安装依赖：
pip3 install -r requirements.txt
这里注意是v2.2的tag分支，因为官方随时都在更新，主分支可能会存在bug。
进入项目的目录：
cd /Bert-VITS2
随后下载新的底模和情感模型，下载地址：
https://openi.pcl.ac.cn/Stardust_minus/Bert-VITS2/modelmanage/show_model
将新的情感模型clap-hatsat-fused放入到项目的emotional目录，结构如下：
E:\work\Bert-VITS2-v22\emotional>tree /f
Folder PATH listing for volume myssd
Volume serial number is 7CE3-15AE
E:.
├───clap-htsat-fused
│ .gitattributes
│ config.json
│ merges.txt
│ preprocessor_config.json
│ pytorch_model.bin
│ README.md
│ special_tokens_map.json
│ tokenizer.json
│ tokenizer_config.json
│ vocab.json
│
└───wav2vec2-large-robust-12-ft-emotion-msp-dim
.gitattributes
config.json
LICENSE
preprocessor_config.json
pytorch_model.bin
README.md
vocab.json
注意，wav2vec2-large-robust-12-ft-emotion-msp-dim是Bert-vits2-v2.1的情感模型，也需要保留，具体请移步：义无反顾马督工,Bert-vits2V210复刻马督工实践(Python3.10)， 这里不再赘述。
至此，新模型就配置好了。
Bert-vits2-v2.2模型训练
首先下载训练集，以原神角色八重神子的英文配音为例子，数据集下载地址：
https://github.com/AI-Hobbyist/Genshin_Datasets
随后新建miko角色目录
mkdir miko
将语音标注文件以esd.list命名，放入miko目录。
同时将分片语音素材放入raw目录。
最后新建miko/configs/config.json配置文件：
{
"train": {
"log_interval": 50,
"eval_interval": 50,
"seed": 42,
"epochs": 1000,
"learning_rate": 0.0002,
"betas": [
0.8,
0.99
],
"eps": 1e-09,
"batch_size": 6,
"fp16_run": false,
"lr_decay": 0.99995,
"segment_size": 16384,
"init_lr_ratio": 1,
"warmup_epochs": 0,
"c_mel": 45,
"c_kl": 1.0,
"skip_optimizer": false,
"freeze_ZH_bert": false,
"freeze_JP_bert": false,
"freeze_EN_bert": false
},
"data": {
"training_files": "data/miko/train.list",
"validation_files": "data/miko/val.list",
"max_wav_value": 32768.0,
"sampling_rate": 44100,
"filter_length": 2048,
"hop_length": 512,
"win_length": 2048,
"n_mel_channels": 128,
"mel_fmin": 0.0,
"mel_fmax": null,
"add_blank": true,
"n_speakers": 1,
"cleaned_text": true,
"spk2id": {
"miko": 0
}
},
"model": {
"use_spk_conditioned_encoder": true,
"use_noise_scaled_mas": true,
"use_mel_posterior_encoder": false,
"use_duration_discriminator": true,
"inter_channels": 192,
"hidden_channels": 192,
"filter_channels": 768,
"n_heads": 2,
"n_layers": 6,
"kernel_size": 3,
"p_dropout": 0.1,
"resblock": "1",
"resblock_kernel_sizes": [
3,
7,
11
],
"resblock_dilation_sizes": [
[
1,
3,
5
],
[
1,
3,
5
],
[
1,
3,
5
]
],
"upsample_rates": [
8,
8,
2,
2,
2
],
"upsample_initial_channel": 512,
"upsample_kernel_sizes": [
16,
16,
8,
2,
2
],
"n_layers_q": 3,
"use_spectral_norm": false,
"gin_channels": 256
},
"version": "2.2"
}
这里注意"version": "2.2"，即版本号为最新的v2.2。
其他参数根据当前的设备环境酌情调整即可。
随后启动预处理页面：
python3 webui_preprocess.py
访问http://127.0.0.1:7860/:
按照页面的步骤进行操作即可，简单且方便。
操作完之后，运行训练命令：
python3 train_ms.py
训练好的模型放在data/miko/models目录，结构如下：
E:\work\Bert-VITS2-v22\Data\miko\models>tree /f
Folder PATH listing for volume myssd
Volume serial number is 7CE3-15AE
E:.
│ DUR_0.pth
│ DUR_100.pth
│ DUR_150.pth
│ DUR_50.pth
│ D_0.pth
│ D_100.pth
│ D_150.pth
│ D_50.pth
│ events.out.tfevents.1702457087.ly.13044.0
│ events.out.tfevents.1702458207.ly.12416.0
│ githash
│ G_0.pth
│ G_100.pth
│ G_150.pth
│ G_50.pth
│ train.log
│
└───eval
events.out.tfevents.1702457087.ly.13044.1
events.out.tfevents.1702458207.ly.12416.1
至此，训练环节结束。
Bert-vits2-v2.2模型推理
推理我们使用Bert-vits2-UI项目的页面，克隆web项目：
git clone https://github.com/jiangyuxiaoxiao/Bert-VITS2-UI
将Web项目放入Bert-vits2-v2.2的根目录中，目录结构如下：
E:\work\Bert-VITS2-v22_lilith\Web>tree /f
Folder PATH listing for volume myssd
Volume serial number is 7CE3-15AE
E:.
│ index.html
│
├───assets
│ index-21bc6a28.css
│ index-402c0217.js
│
└───img
helps1.png
helps2.png
Hiyori.ico
这里包含主页面、样式文件以及JS文件，基于Hiyori。
随后启动推理页面:
python3 server_fastapi.py
加载模型进行推理即可。
此外，还可以基于FastAPI的接口进行推理，换句话说，发送http请求即可获取推理音频，接口参数如下：
{
"openapi": "3.1.0",
"info": {
"title": "FastAPI",
"version": "0.1.0"
},
"paths": {
"/": {
"get": {
"summary": "Index",
"operationId": "index__get",
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
}
}
}
},
"/voice": {
"post": {
"summary": "Voice",
"description": "语音接口，若需要上传参考音频请仅使用post请求",
"operationId": "voice_voice_post",
"parameters": [
{
"name": "model_id",
"in": "query",
"required": true,
"schema": {
"type": "integer",
"description": "模型ID",
"title": "Model Id"
},
"description": "模型ID"
},
{
"name": "speaker_name",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "说话人名",
"title": "Speaker Name"
},
"description": "说话人名"
},
{
"name": "speaker_id",
"in": "query",
"required": false,
"schema": {
"type": "integer",
"description": "说话人id，与speaker_name二选一",
"title": "Speaker Id"
},
"description": "说话人id，与speaker_name二选一"
},
{
"name": "sdp_ratio",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "SDP/DP混合比",
"default": 0.2,
"title": "Sdp Ratio"
},
"description": "SDP/DP混合比"
},
{
"name": "noise",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "感情",
"default": 0.2,
"title": "Noise"
},
"description": "感情"
},
{
"name": "noisew",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "音素长度",
"default": 0.9,
"title": "Noisew"
},
"description": "音素长度"
},
{
"name": "length",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "语速",
"default": 1,
"title": "Length"
},
"description": "语速"
},
{
"name": "language",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "语言",
"title": "Language"
},
"description": "语言"
},
{
"name": "auto_translate",
"in": "query",
"required": false,
"schema": {
"type": "boolean",
"description": "自动翻译",
"default": false,
"title": "Auto Translate"
},
"description": "自动翻译"
},
{
"name": "auto_split",
"in": "query",
"required": false,
"schema": {
"type": "boolean",
"description": "自动切分",
"default": false,
"title": "Auto Split"
},
"description": "自动切分"
},
{
"name": "emotion",
"in": "query",
"required": false,
"schema": {
"anyOf": [
{
"type": "integer"
},
{
"type": "string"
},
{
"type": "null"
}
],
"description": "emo",
"title": "Emotion"
},
"description": "emo"
}
],
"requestBody": {
"required": true,
"content": {
"multipart/form-data": {
"schema": {
"$ref": "#/components/schemas/Body_voice_voice_post"
}
}
}
},
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
},
"get": {
"summary": "Voice",
"description": "语音接口",
"operationId": "voice_voice_get",
"parameters": [
{
"name": "text",
"in": "query",
"required": true,
"schema": {
"type": "string",
"description": "输入文字",
"title": "Text"
},
"description": "输入文字"
},
{
"name": "model_id",
"in": "query",
"required": true,
"schema": {
"type": "integer",
"description": "模型ID",
"title": "Model Id"
},
"description": "模型ID"
},
{
"name": "speaker_name",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "说话人名",
"title": "Speaker Name"
},
"description": "说话人名"
},
{
"name": "speaker_id",
"in": "query",
"required": false,
"schema": {
"type": "integer",
"description": "说话人id，与speaker_name二选一",
"title": "Speaker Id"
},
"description": "说话人id，与speaker_name二选一"
},
{
"name": "sdp_ratio",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "SDP/DP混合比",
"default": 0.2,
"title": "Sdp Ratio"
},
"description": "SDP/DP混合比"
},
{
"name": "noise",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "感情",
"default": 0.2,
"title": "Noise"
},
"description": "感情"
},
{
"name": "noisew",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "音素长度",
"default": 0.9,
"title": "Noisew"
},
"description": "音素长度"
},
{
"name": "length",
"in": "query",
"required": false,
"schema": {
"type": "number",
"description": "语速",
"default": 1,
"title": "Length"
},
"description": "语速"
},
{
"name": "language",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "语言",
"title": "Language"
},
"description": "语言"
},
{
"name": "auto_translate",
"in": "query",
"required": false,
"schema": {
"type": "boolean",
"description": "自动翻译",
"default": false,
"title": "Auto Translate"
},
"description": "自动翻译"
},
{
"name": "auto_split",
"in": "query",
"required": false,
"schema": {
"type": "boolean",
"description": "自动切分",
"default": false,
"title": "Auto Split"
},
"description": "自动切分"
},
{
"name": "emotion",
"in": "query",
"required": false,
"schema": {
"anyOf": [
{
"type": "integer"
},
{
"type": "string"
},
{
"type": "null"
}
],
"description": "emo",
"title": "Emotion"
},
"description": "emo"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/models/info": {
"get": {
"summary": "Get Loaded Models Info",
"description": "获取已加载模型信息",
"operationId": "get_loaded_models_info_models_info_get",
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
}
}
}
},
"/models/delete": {
"get": {
"summary": "Delete Model",
"description": "删除指定模型",
"operationId": "delete_model_models_delete_get",
"parameters": [
{
"name": "model_id",
"in": "query",
"required": true,
"schema": {
"type": "integer",
"description": "删除模型id",
"title": "Model Id"
},
"description": "删除模型id"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/models/add": {
"get": {
"summary": "Add Model",
"description": "添加指定模型：允许重复添加相同路径模型，且不重复占用内存",
"operationId": "add_model_models_add_get",
"parameters": [
{
"name": "model_path",
"in": "query",
"required": true,
"schema": {
"type": "string",
"description": "添加模型路径",
"title": "Model Path"
},
"description": "添加模型路径"
},
{
"name": "config_path",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "添加模型配置文件路径，不填则使用./config.json或../config.json",
"title": "Config Path"
},
"description": "添加模型配置文件路径，不填则使用./config.json或../config.json"
},
{
"name": "device",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "推理使用设备",
"default": "cuda",
"title": "Device"
},
"description": "推理使用设备"
},
{
"name": "language",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "模型默认语言",
"default": "ZH",
"title": "Language"
},
"description": "模型默认语言"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/models/get_unloaded": {
"get": {
"summary": "Get Unloaded Models Info",
"description": "获取未加载模型",
"operationId": "get_unloaded_models_info_models_get_unloaded_get",
"parameters": [
{
"name": "root_dir",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "搜索根目录",
"default": "Data",
"title": "Root Dir"
},
"description": "搜索根目录"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/models/get_local": {
"get": {
"summary": "Get Local Models Info",
"description": "获取全部本地模型",
"operationId": "get_local_models_info_models_get_local_get",
"parameters": [
{
"name": "root_dir",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "搜索根目录",
"default": "Data",
"title": "Root Dir"
},
"description": "搜索根目录"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/status": {
"get": {
"summary": "Get Status",
"description": "获取电脑运行状态",
"operationId": "get_status_status_get",
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
}
}
}
},
"/tools/translate": {
"get": {
"summary": "Translate",
"description": "翻译",
"operationId": "translate_tools_translate_get",
"parameters": [
{
"name": "texts",
"in": "query",
"required": true,
"schema": {
"type": "string",
"description": "待翻译文本",
"title": "Texts"
},
"description": "待翻译文本"
},
{
"name": "to_language",
"in": "query",
"required": true,
"schema": {
"type": "string",
"description": "翻译目标语言",
"title": "To Language"
},
"description": "翻译目标语言"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/tools/random_example": {
"get": {
"summary": "Random Example",
"description": "获取一个随机音频+文本，用于对比，音频会从本地目录随机选择。",
"operationId": "random_example_tools_random_example_get",
"parameters": [
{
"name": "language",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "指定语言，未指定则随机返回",
"title": "Language"
},
"description": "指定语言，未指定则随机返回"
},
{
"name": "root_dir",
"in": "query",
"required": false,
"schema": {
"type": "string",
"description": "搜索根目录",
"default": "Data",
"title": "Root Dir"
},
"description": "搜索根目录"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
},
"/tools/get_audio": {
"get": {
"summary": "Get Audio",
"operationId": "get_audio_tools_get_audio_get",
"parameters": [
{
"name": "path",
"in": "query",
"required": true,
"schema": {
"type": "string",
"description": "本地音频路径",
"title": "Path"
},
"description": "本地音频路径"
}
],
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/HTTPValidationError"
}
}
}
}
}
}
}
},
"components": {
"schemas": {
"Body_voice_voice_post": {
"properties": {
"text": {
"type": "string",
"title": "Text"
},
"reference_audio": {
"type": "string",
"format": "binary",
"title": "Reference Audio"
}
},
"type": "object",
"required": [
"text"
],
"title": "Body_voice_voice_post"
},
"HTTPValidationError": {
"properties": {
"detail": {
"items": {
"$ref": "#/components/schemas/ValidationError"
},
"type": "array",
"title": "Detail"
}
},
"type": "object",
"title": "HTTPValidationError"
},
"ValidationError": {
"properties": {
"loc": {
"items": {
"anyOf": [
{
"type": "string"
},
{
"type": "integer"
}
]
},
"type": "array",
"title": "Location"
},
"msg": {
"type": "string",
"title": "Message"
},
"type": {
"type": "string",
"title": "Error Type"
}
},
"type": "object",
"required": [
"loc",
"msg",
"type"
],
"title": "ValidationError"
}
}
}
}
最后奉上Bert-vits2-v2.2本地训练推理整合包：
https://pan.baidu.com/s/1OVX9seRwZR6bZ-xsE_nRLg?pwd=v3uc
与众乡亲同飨。
Bert-vits2-v2.2新版本本地训练推理整合包(原神八重神子英文模型miko)的更多相关文章
- Bert不完全手册8. 预训练不要停！Continue Pretraining
paper: Don't stop Pretraining: Adapt Language Models to Domains and Tasks GitHub: https://github.com ...
- DeepSpeed Chat: 一键式RLHF训练，让你的类ChatGPT千亿大模型提速省钱15倍
DeepSpeed Chat: 一键式RLHF训练,让你的类ChatGPT千亿大模型提速省钱15倍 1. 概述 近日来,ChatGPT及类似模型引发了人工智能(AI)领域的一场风潮. 这场风潮对数字世 ...
- maven向本地仓库导入jar包（处理官网没有的jar包）
对于官网没有的jar包,maven向本地仓库导入jar包用如下命令 mvn install:install-file -DgroupId=包名 -DartifactId=项目名 -Dversion=版 ...
- Intellij IDEA 像eclipse那样给maven添加依赖，且Intellij idea里在pom.xml里添加Maven依赖，本地仓库下拉列表显示包很少的血的经验
打开pom.xml,在它里面使用快捷键:ALT+Insert ————>点击dependency 再输入想要添加的依赖关键字,比如:输个spring 出现下图: 根据需求选择版本,完成以后 ...
- 网络编程 -- RPC实现原理 -- RPC -- 迭代版本V2 -- 本地方法调用 整合 Spring
网络编程 -- RPC实现原理 -- 目录 啦啦啦 V2——RPC -- 本地方法调用 + Spring 1. 配置applicationContext.xml文件 注入 bean 及 管理 bean ...
- xmake v2.2.2, 让C/C++拥有包依赖自动构建
前言 历经四个多月,xmake终于更新了新版本v2.2.2,并且上线了重量级功能:原生支持的远程依赖包管理. 而这个特性,其实我陆陆续续写了将近一年的时间,才初步完成,对于此特性的开发进展和历史,有兴 ...
- Maven打包时囊括本地依赖的jar包
在开发中,偶尔会遇到一个问题:某些比较冷门的包,maven服务器上没有,而我们又必须用,通常情况下会在项目中建立一个lib文件夹.将这些包copy进去并加入buildpath,开发就可以继续了,如下图 ...
- virtualbox中新版本Ubuntu安装软件增强包后重启无限登录界面的解决办法
原来我虚拟机版本是4.2.10,装的Ubuntu3.3,因为版本过老使用出现了一些问题,于是换成14.04,安装成功,但是装增强包的时候,装完重启,无限登录界面,密码是对的. 看了网上的很多方法,什么 ...
- nexus私服服务器意外关机后，本地不能下载jar包
主要记录一个小问题. 今天要做个需求,需要读取word文档中的表格来在生成数据库建表语句. 读取word文档,要添加maven依赖 <dependency> <groupId> ...
- maven引入本地jar 打jar包
没搭建私服的情况下引入本地的jar,并把本地jar打包进项目的run jar 以打包引入hadoop-common-2.7.5.jar为例 引用 复制jar包所在的路径 打开cmd命令提示符 切换路径 ...
随机推荐
- 深入理解Linux内核——内存管理（1）
提要:本系列文章主要参考MIT 6.828课程以及两本书籍<深入理解Linux内核> <深入Linux内核架构>对Linux内核内容进行总结. 内存管理的实现覆盖了多个领域: ...
- Poor God Water（ACM-ICPC 2018 焦作赛区网络预赛 矩阵快速幂）
题目描述 God Water likes to eat meat, fish and chocolate very much, but unfortunately, the doctor tells ...
- Hadoop环境安装与配置
1.基础操作系统环境安装(略) 2.JDK的安装与配置 当前各大数据软件如Hadoop等,仍然停留在Java 8上,在本实验选用的是Java 8.在自己的Linux系统中,jdk可以使用如下命令进行一 ...
- KMP字符串对比算法及next数组计算
(注:该贴主要运用python实现该算法) 先谈谈KMP算法吧.KMP算法的全称是Knuth-Morris-Pratt 算法,它是用来进行字符串查找,即在某个主字符串里面找到某个特定子字符串.但是好像 ...
- 探索计算机的I/O控制方式：了解DMA控制器的作用与优势
I/O控制方式 在前面我们已经了解到,每个设备都配备了一个设备控制器.当CPU向设备控制器发送命令并将其存储在寄存器中时,设备控制器会执行相应的操作.然而,尽管设备控制器会更新状态寄存器的状态,但是如 ...
- zbolg首页-文章内标签调用代码
{if count($lhantItem.Tags)>0}{foreach $lhantItem.Tags as $i => $tag} <a href='{$tag.Url}' t ...
- Goobye, cnblogs
转 typecho 了,个人网站的客制化程度当然不是 cnblogs 能比得上的. <cirnovsky.cf>
- filebeat新filestream类型是否支持tail_files类似功能探究
背景 试水搭建ELK,使用了ELK7.17.13版本,filebeat默认配置的input type已经是filestream而非旧版的log类型,开始了探索之旅. 信任ChatGPT导致的三次失败尝 ...
- Tinyalsa PCM API 实现深度剖析
高级 Linux 音频架构 (ALSA) 用于为 Linux 操作系统提供音频和 MIDI 功能.它可以高效地支持所有类型的音频接口,从消费者声卡到专业的多通道音频接口.它支持全模块化的音频驱动.它是 ...
- 惊奇！Android studio内部在调用Eclipse
现在用Android studio的人越来越多,主要是说谷歌不再支持Eclipse,而力推Android studio.但是as也太不给力了,我之前写过一篇博客提到. 今天要说的是一个惊天的消息,如题 ...