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MockingBird

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AI 模型与开发框架图像、视频与音频内容创作与媒体工具 aideep-learningpytorchspeechtext-to-speechtts
36,873
Stars
5,149
Forks
298
Watchers
481
Open Issues
NOASSERTION
许可证
Python
语言
2021-08-07
创建时间
2026-03-03
最近更新

项目能做什么

仅需 5 秒即可克隆声音,并实时生成任意语音的开源工具。
来源:基于仓库元数据 · 内容以仓库实际 README 为准

使用说明 查看原始 README 原仓库文档

中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
> 🚧 While I no longer actively update this repo, you can find me continuously pushing this tech forward to good side and open-source. I'm also building an optimized and cloud hosted version: https://noiz.ai/ and [we're hiring](https://github.com/babysor/MockingBird/issues/1029).
>
![mockingbird](https://user-images.githubusercontent.com/12797292/131216767-6eb251d6-14fc-4951-8324-2722f0cd4c63.jpg)
<a href="https://trendshift.io/repositories/3869" target="_blank"><img src="https://trendshift.io/api/badge/repositories/3869" alt="babysor%2FMockingBird | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](http://choosealicense.com/licenses/mit/)

> English | [中文](README-CN.md)| [中文Linux](README-LINUX-CN.md)

## Features
🌍 **Chinese** supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata, aishell3, data_aishell, and etc.

🤩 **PyTorch** worked for pytorch, tested in version of 1.9.0(latest in August 2021), with GPU Tesla T4 and GTX 2060

🌍 **Windows + Linux** run in both Windows OS and linux OS (even in M1 MACOS)

🤩 **Easy & Awesome** effect with only newly-trained synthesizer, by reusing the pretrained encoder/vocoder

🌍 **Webserver Ready** to serve your result with remote calling

### [DEMO VIDEO](https://www.bilibili.com/video/BV17Q4y1B7mY/)

## Quick Start

### 1. Install Requirements
#### 1.1 General Setup
> Follow the original repo to test if you got all environment ready.
**Python 3.7 or higher ** is needed to run the toolbox.

* Install [PyTorch](https://pytorch.org/get-started/locally/).
> If you get an `ERROR: Could not find a version that satisfies the requirement torch==1.9.0+cu102 (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2 )` This error is probably due to a low version of python, try using 3.9 and it will install successfully
* Install [ffmpeg](https://ffmpeg.org/download.html#get-packages).
* Run `pip install -r requirements.txt` to install the remaining necessary packages.
> The recommended environment here is `Repo Tag 0.0.1` `Pytorch1.9.0 with Torchvision0.10.0 and cudatoolkit10.2` `requirements.txt` `webrtcvad-wheels` because `requirements. txt` was exported a few months ago, so it doesn't work with newer versions
* Install webrtcvad `pip install webrtcvad-wheels`(If you need)

or
- install dependencies with `conda` or `mamba`

  ```conda env create -n env_name -f env.yml```

  ```mamba env create -n env_name -f env.yml```

  will create a virtual environment where necessary dependencies are installed. Switch to the new environment by `conda activate env_name` and enjoy it.
  > env.yml only includes the necessary dependencies to run the project,temporarily without monotonic-align. You can check the official website to install the GPU version of pytorch.

#### 1.2 Setup with a M1 Mac
> The following steps are a workaround to directly use the original `demo_toolbox.py`without the changing of codes.
>
阅读完整原文

商业机会分析 规则生成(AI 未配置)

综合评分 43.9 分。该项目在“个人可实施性”维度得 20 分,“付费可能性”维度得 20.0 分,差异化空间 94.0 分(评分依据见评分卡)。

面向细分需求的二次开发产品

产品构想基于 MockingBird 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。
目标用户该细分场景用户
难度/周期中 · 2~6 周
收费模式买断制 / 订阅制 / 广告
竞争风险细分需求规模需验证
依据 AI 推测:基于项目主题标签的判断
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心

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以上为通过 GitHub 官方 Search API 检索的相似项目,功能差异与优劣势需进一步人工确认,配置 AI 后可生成对比分析。

项目优势与风险

技术成熟度创建于 2021-08-07,最近推送 2026-03-03,发布过 1 个 Release
社区活跃Star 36,873 / Fork 5,149 / Issue 481(数据支持,可自行核实)
许可证NOASSERTION
主要风险上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价

安装与使用

快速开始(以仓库 README 为准)
git clone https://github.com/babysor/MockingBird.git
cd MockingBird
# 请阅读仓库 README 获取确切安装步骤(依赖、配置、启动命令)
阅读原仓库文档
术语说明:Docker=应用容器(把程序和依赖打包运行);API Key=调用外部服务的密钥;Git Clone=把仓库代码下载到本地。常见错误:API Key 未配置 / 端口占用 / 数据库连接失败,多数项目在 README 的 Troubleshooting 章节有说明。