{"data":{"slug":"digitalphonetics-ims-toucan","name":"IMS-Toucan","tagline":"Controllable and fast Text-to-Speech for over 7000 languages!","github_url":"https://github.com/DigitalPhonetics/IMS-Toucan","owner":"DigitalPhonetics","repo":"IMS-Toucan","owner_avatar_url":"https://avatars.githubusercontent.com/u/42207404?v=4","primary_language":"Python","stars":2204,"forks":317,"topics":["deep-learning","pytorch","speech","speech-processing","speech-synthesis","text-to-speech","toolkit","tts"],"archived":false,"github_pushed_at":"2026-01-25T14:45:14+00:00","maintenance_label":"Slowing","url":"https://www.graphcanon.com/tools/digitalphonetics-ims-toucan","markdown_url":"https://www.graphcanon.com/tools/digitalphonetics-ims-toucan.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/digitalphonetics-ims-toucan","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=digitalphonetics-ims-toucan","description":"Controllable and fast Text-to-Speech for over 7000 languages!","homepage_url":null,"license":"Apache-2.0","open_issues":3,"watchers":25,"ai_summary":null,"readme_excerpt":"## Installation 🦉\n\n#### Basic Requirements\n\nPython 3.10 is the recommended version.\n\nTo install this toolkit, clone it onto the machine you want to use it on\n(should have at least one cuda enabled GPU if you intend to train models on that machine. For inference, you don't need\na GPU).\n\nIf you're using Linux, you should have the following packages installed, or install them with apt-get if you haven't (on\nmost distributions they come pre-installed):\n\n```\nlibsndfile1\nespeak-ng\nffmpeg\nlibasound-dev\nlibportaudio2\nlibsqlite3-dev\n```\n\nNavigate to the directory you have cloned. We recommend creating and activating a\n[virtual environment](https://docs.python.org/3/library/venv.html)\nto install the basic requirements into. The commands below summarize everything you need to do under Linux. If you are\nrunning Windows, the second line needs to be changed, please have a look at\nthe [venv documentation](https://docs.python.org/3/library/venv.html).\n\n```\npython -m venv <path_to_where_you_want_your_env_to_be>\n\nsource <path_to_where_you_want_your_env_to_be>/bin/activate\n\npip install --no-cache-dir -r requirements.txt\n```\n\nRun the second line everytime you start using the tool again to activate the virtual environment again, if you e.g.\nlogged out in the meantime. To make use of a GPU, you don't need to do anything else on a Linux machine. On a Windows\nmachine, have a look at [the official PyTorch website](https://pytorch.org/) for the install-command that enables GPU\nsupport.\n\n#### Storage configuration\n\nIf you don't want the pretrained and trained models as well as the cache files resulting from preprocessing your\ndatasets to be stored in the default subfolders, you can set corresponding directories globally by\nediting `Utility/storage_config.py` to suit your needs (the path can be relative to the repository root directory or\nabsolute).\n\n#### Pretrained Models\n\nYou don't need to use pretrained models, but it can speed things up tremendously. They will be downloaded on the fly\nautomatically when they are needed, thanks to Hugging Face🤗 and [VB](https://github.com/Vaibhavs10) in particular.\n\n#### \\[optional] eSpeak-NG\n\neSpeak-NG is an optional requirement, that handles lots of special cases in many languages, so it's good to have.\n\nOn most **Linux** environments it will be installed already, and if it is not, and you have the sufficient rights, you\ncan install it by simply running\n\n```\napt-get install espeak-ng\n```\n\nFor **Windows**, they provide a convenient .msi installer file\n[on their GitHub release page](https://github.com/espeak-ng/espeak-ng/releases). After installation on non-linux\nsystems, you'll also need to tell the phonemizer library where to find your espeak installation by setting the\n`PHONEMIZER_ESPEAK_LIBRARY` environment variable, which is discussed in\n[this issue](https://github.com/bootphon/phonemizer/issues/44#issuecomment-1008449718).\n\nFor **Mac** it's unfortunately a lot more complicated. Thanks to Sang Hyun Park, here is a guide for installing it on\nMac:\nFor M1 Macs, the most convenient method to install espeak-ng onto your system is via a\n[MacPorts port of espeak-ng](https://ports.macports.org/port/espeak-ng/). MacPorts itself can be installed from the\n[MacPorts website](https://www.macports.org/install.php), which also requires Apple's\n[XCode](https://developer.apple.com/xcode/). Once XCode and MacPorts have been installed, you can install the port of\nespeak-ng via\n\n```\nsudo port install espeak-ng\n```\n\nAs stated in the Windows install instructions, the espeak-ng installation will need to be set as a variable for the\nphonemizer library. The environment variable is `PHONEMIZER_ESPEAK_LIBRARY` as given in the\n[GitHub thread](https://github.com/bootphon/phonemizer/issues/44#issuecomment-1008449718) linked above.\nHowever, the espeak-ng installation file you need to set this variable to is a .dylib file rather than a .dll file on\nMac. In order to locate the espeak-ng library file, you can run `port contents espeak-ng`. The","github_created_at":"2021-08-05T10:12:38+00:00","created_at":"2026-07-11T12:09:12.38483+00:00","updated_at":"2026-07-11T12:09:18.066295+00:00","categories":[{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"deep-learning","name":"deep-learning"},{"slug":"toolkit","name":"toolkit"},{"slug":"text-to-speech","name":"text-to-speech"},{"slug":"speech","name":"speech"},{"slug":"tts","name":"tts"},{"slug":"speech-processing","name":"speech-processing"},{"slug":"pytorch","name":"pytorch"},{"slug":"speech-synthesis","name":"speech-synthesis"}],"trust":{"provenance":{"is_fork":false,"github_id":392995634,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T12:09:13.025Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":166,"last_release_at":"2024-10-07T13:22:58Z"},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T12:09:14.097Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T12:09:13.744Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-11T12:09:13.744Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T12:09:13.744Z"}}}}