{"data":{"slug":"babysor-mockingbird","name":"MockingBird","tagline":"Clone a voice in 5 seconds to generate arbitrary speech in real-time","github_url":"https://github.com/babysor/MockingBird","owner":"babysor","repo":"MockingBird","owner_avatar_url":"https://avatars.githubusercontent.com/u/7423248?v=4","primary_language":"Python","stars":36906,"forks":5178,"topics":["ai","deep-learning","pytorch","speech","text-to-speech","tts"],"archived":false,"github_pushed_at":"2026-03-03T14:59:58+00:00","maintenance_label":"Slowing","stars_delta_30d":-7,"url":"https://www.graphcanon.com/tools/babysor-mockingbird","markdown_url":"https://www.graphcanon.com/tools/babysor-mockingbird.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/babysor-mockingbird","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=babysor-mockingbird","description":"🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time","homepage_url":null,"license":"Other","open_issues":481,"watchers":304,"ai_summary":"A Python-based repository using PyTorch for text-to-speech (TTS) and speech cloning.","readme_excerpt":"### 1. Install Requirements\n#### 1.1 General Setup\n> Follow the original repo to test if you got all environment ready.\n**Python 3.7 or higher ** is needed to run the toolbox.\n\n* Install [PyTorch](https://pytorch.org/get-started/locally/).\n> 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\n* Install [ffmpeg](https://ffmpeg.org/download.html#get-packages).\n* Run `pip install -r requirements.txt` to install the remaining necessary packages.\n> 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\n* Install webrtcvad `pip install webrtcvad-wheels`(If you need)\n\nor\n- install dependencies with `conda` or `mamba`\n\n  ```conda env create -n env_name -f env.yml```\n\n  ```mamba env create -n env_name -f env.yml```\n\n  will create a virtual environment where necessary dependencies are installed. Switch to the new environment by `conda activate env_name` and enjoy it.\n  > 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.\n\n#### 1.2 Setup with a M1 Mac\n> The following steps are a workaround to directly use the original `demo_toolbox.py`without the changing of codes.\n>\n  >  Since the major issue comes with the PyQt5 packages used in `demo_toolbox.py` not compatible with M1 chips, were one to attempt on training models with the M1 chip, either that person can forgo `demo_toolbox.py`, or one can try the `web.py` in the project.\n\n##### 1.2.1 Install `PyQt5`, with [ref](https://stackoverflow.com/a/68038451/20455983) here.\n  * Create and open a Rosetta Terminal, with [ref](https://dev.to/courier/tips-and-tricks-to-setup-your-apple-m1-for-development-547g) here.\n  * Use system Python to create a virtual environment for the project\n    ```\n    /usr/bin/python3 -m venv /PathToMockingBird/venv\n    source /PathToMockingBird/venv/bin/activate\n    ```\n  * Upgrade pip and install `PyQt5`\n    ```\n    pip install --upgrade pip\n    pip install pyqt5\n    ```\n##### 1.2.2 Install `pyworld` and `ctc-segmentation`\n\n> Both packages seem to be unique to this project and are not seen in the original [Real-Time Voice Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning) project. When installing with `pip install`, both packages lack wheels so the program tries to directly compile from c code and could not find `Python.h`.\n\n  * Install `pyworld`\n      * `brew install python` `Python.h` can come with Python installed by brew\n      * `export CPLUS_INCLUDE_PATH=/opt/homebrew/Frameworks/Python.framework/Headers` The filepath of brew-installed `Python.h` is unique to M1 MacOS and listed above. One needs to manually add the path to the environment variables.\n      * `pip install pyworld` that should do.\n\n\n  * Install`ctc-segmentation`\n    > Same method does not apply to `ctc-segmentation`, and one needs to compile it from the source code on [github](https://github.com/lumaku/ctc-segmentation).\n    * `git clone https://github.com/lumaku/ctc-segmentation.git`\n    * `cd ctc-segmentation`\n    * `source /PathToMockingBird/venv/bin/activate` If the virtual environment hasn't been deployed, activate it.\n    * `cythonize -3 ctc_segmentation/ctc_segmentation_dyn.pyx`\n    * `/usr/bin/arch -x86_64 python setup.py build` Build with x86 architecture.\n    * `/usr/bin/arch -x86_64 python setup.py install --optimize=1 --skip-build`Install with x86 architecture.\n\n##### 1.2.3 Other dependencies\n  * `/usr/bin/arch -x86_64 pip install torch torchvision torchaudio` Pip installing `PyTorch` as an example, articulate that it's installed with x86 architecture\n  * `pip install f","github_created_at":"2021-08-07T03:53:39+00:00","created_at":"2026-07-11T12:03:49.066069+00:00","updated_at":"2026-09-20T07:02:28.387262+00:00","categories":[{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"pytorch","name":"pytorch"},{"slug":"speech","name":"speech"},{"slug":"text-to-speech","name":"text-to-speech"},{"slug":"tts","name":"tts"}],"trust":{"provenance":{"is_fork":false,"github_id":393571599,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T07:02:25.655Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":200,"last_release_at":"2021-11-07T13:53:53Z","stars_delta_30d":-7,"open_issues_delta_30d":-1},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":4,"high_count":0,"last_scan_at":"2026-07-11T12:03:51.193Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T07:02:27.097Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T07:02:27.097Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-09-20T07:02:27.097Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T07:02:27.097Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-09-20T07:02:27.097Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Use MockingBird when you require rapid voice cloning, as it claims to clone voices in just five seconds.","Consider MockingBird if real-time arbitrary speech generation is a priority for your project.","Choose this tool for Python projects that need text-to-speech functionality and are willing to follow detailed setup instructions."],"when_not_to_use":["Avoid MockingBird if you are working with a version of Python lower than 3.7, as it explicitly requires newer versions to function correctly.","Do not use this tool if your environment does not support PyTorch1.9.0 and cudatoolkit10.2, needed for project requirements.","If you need the tool to run natively on M1 Macs without workarounds, MockingBird might not be suitable without additional compatibility steps."],"source":"enrich:decision_facts","observed_at":"2026-07-17T12:58:46.406Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"MockingBird is a Python-based tool for text-to-speech and speech cloning using PyTorch that offers real-time speech generation."}]}}