ToucanTTS

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Introduce：

ToucanTTS is a multilingual and controllable text-to-speech synthesis toolkit developed by the Institute for Natural Language Processing at the University of Stuttgart in Germany. It is built using pure Python and PyTorch to keep it simple and easy to get started while being as powerful as possible. The toolkit supports teaching, training, and use of cutting-edge speech synthesis models with a high degree of flexibility and customizability for both education and research.

Stakeholders:
ToucanTTS is aimed at researchers, educators and students in the field of speech technology. It is suitable for professionals who need to conduct speech synthesis research, develop multilingual speech applications, or teach speech technology. Due to its ease of use and powerful features, it is also suitable for beginners to learn and explore speech synthesis techniques.
Usage Scenario Examples:

• Use ToucanTTS to teach speech synthesis principles in university courses
• Researchers use the toolkit to develop new speech synthesis algorithms
• Educators use ToucanTTS to show students the effects of speech synthesis in different languages

The features of the tool:

• Supports text-to-speech synthesis for multiple languages and speech
• Download pre-trained models to speed up research and development
• Support custom language embedding and speaker embedding to achieve personalized speech synthesis
• Provides interactive presentations and audio generation interfaces for easy teaching and presentation
• Supports training models from scratch or fine-tuning based on pre-trained models
• Provide detailed installation and use guidelines to reduce the threshold of use

Steps for Use:

• 1. Clone the ToucanTTS tool package to the local machine
• 2. Create and activate virtual environments to install basic dependencies
• 3. Configure the storage path and pre-training model as required
• 4. Download the pre-training model using the provided script
• 5. Through the InferenceInterfaces/ToucanTTSInterface. Liy and speech synthesis load model
• 6. Use the provided sample scripts or API interfaces for custom development and integration

Tool’s Tabs: Text to speech, speech synthesis