Zonos
by ZyphraZonos is a high-fidelity text-to-speech (TTS) model developed by Zyphra. It includes two models: a 1.6 billion parameter Transformer model and an SSM hybrid model, both open-sourced under the Apache 2.0 license. Zonos generates natural and expressive speech based on text prompts and speaker embeddings, supporting voice cloning and adjustable parameters such as speed, pitch, and emotion. The output sampling rate is 44kHz. The model is trained on approximately 200,000 hours of multilingual speech data, primarily supporting English with limited support for other languages. Zonos provides an optimized inference engine for fast speech generation, making it suitable for real-time applications.
What is Zonos?
Zonos is a high-fidelity text-to-speech (TTS) model developed by Zyphra. It includes two models: a 1.6 billion parameter Transformer model and an SSM hybrid model, both open-sourced under the Apache 2.0 license. Zonos generates natural and expressive speech based on text prompts and speaker embeddings, supporting voice cloning and adjustable parameters such as speed, pitch, and emotion. The output sampling rate is 44kHz. The model is trained on approximately 200,000 hours of multilingual speech data, primarily supporting English with limited support for other languages. Zonos provides an optimized inference engine for fast speech generation, making it suitable for real-time applications.
Main Features of Zonos
- Zero-shot TTS and Voice Cloning: Input text and a 10-30 second speaker sample to generate high-quality TTS output.
- Audio Prefix Input: Add text and audio prefixes to more accurately match the speaker's voice and replicate behaviors like whispering that are difficult to achieve with speaker embeddings alone.
- Multilingual Support: Supports English, Japanese, Chinese, French, and German.
- Audio Quality and Emotion Control: Fine-tune parameters such as speed, pitch, maximum frequency, audio quality, and various emotions.
Technical Principles of Zonos
- Text Preprocessing: Normalize and phonemize input text using the eSpeak tool, converting it into a sequence of phonemes.
- Feature Prediction: Use a Transformer or hybrid backbone network to predict DAC (Discrete Audio Codec) tokens.
- Speech Generation: Decode the predicted DAC tokens using an autoencoder to generate high-quality speech output.
Zonos Project Address
- Project Website: https://www.zyphra.com/post/beta-release-of-zonos-v0-1
- GitHub Repository: https://github.com/Zyphra/Zonos
Application Scenarios of Zonos
- Audiobooks and Online Education: Convert text content into natural and fluent speech, providing high-quality voiceovers for audiobooks and online courses.
- Virtual Assistants and Customer Service: Generate natural speech interactions in virtual assistants and customer service systems, offering a more human-like user experience.
- Multimedia Content Creation: Produce high-quality voiceovers and dubbing for video production, animation, and advertising.
- Accessibility Technology: Provide voice reading services for visually impaired individuals, converting web pages, documents, and books into speech to help them better access information.
- Gaming and Interactive Entertainment: Generate character dialogues and narrations in games and interactive entertainment applications, enhancing the immersive experience.
Model Capabilities
Model Type
Text-to-Speech
Supported Tasks
Voice Cloning
Multilingual Speech Generation
Real-Time Speech Synthesis
Tags
Text-to-Speech
Voice Cloning
Multilingual
Speech Synthesis
AI Models
Natural Language Processing
Real-Time Applications
Open Source
High-Fidelity Audio
Developer Tools
Usage & Integration
Pricing
free
License
Open Source
Apache 2.0
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