F5-TTS - Shanghai Jiao Tong University launches open-source text-to-speech (TTS) synthesis system
F5-TTS is a high-performance text-to-speech (TTS) system open-sourced by Shanghai Jiao Tong University. It is based on a non-autoregressive generation method using stream matching, combined with Diffusion Transformer (DiT) technology. The system can...
What is F5-TTS?
F5-TTS is a high-performance text-to-speech (TTS) system open-sourced by Shanghai Jiao Tong University. It utilizes a non-autoregressive generation method based on stream matching, combined with Diffusion Transformer (DiT) technology. The system rapidly generates natural, fluent, and faithful-to-the-source speech through zero-shot learning without additional supervision. F5-TTS supports multilingual synthesis, including Chinese and English, and can effectively synthesize speech from long texts. F5-TTS features emotion control, adjusting the emotional expression of the synthesized speech based on the text content. It also supports speed control, allowing users to adjust the playback speed as needed. The system was trained on a massive dataset of 100,000 hours, demonstrating excellent performance and generalization ability. F5-TTS has a wide range of applications, including audiobooks, voice assistants, language learning, news broadcasting, and game voice-over, providing powerful speech synthesis capabilities for various commercial and non-commercial uses.
Main functions of F5-TTS
- Zero-sample sound cloningIt can mimic anyone's voice without requiring data from a specific speaker.
- Speed controlThe speech generation speed is adjusted according to the total duration, enabling precise control over the speech playback speed.
- Emotional expression controlControlling the emotional tone of synthesized speech makes machine-generated speech more expressive of human emotions.
- Long text synthesisIt supports continuous speech synthesis of long texts, making it suitable for reading and broadcasting long content.
- Multilingual supportIt can process and generate speech in multiple languages, including Chinese and English, and has excellent multilingual synthesis capabilities.
- Large-scale data trainingTraining was performed on a massive dataset of 100,000 hours to ensure the model's generalization ability and the naturalness of the synthesized speech.
F5-TTS Technical Principles
- Flow MatchingF5-TTS is based on a flow-matching target training model that can transform a simple probability distribution (such as the standard normal distribution) into a more complex probability distribution that approximates the data distribution. This involves training the model across the entire flow step and data range to ensure the smooth handling of the transformation from the initial distribution to the target distribution.
- Diffusion converter (DiT)As the backbone network of the model, DiT can process sequential data and gradually remove noise during the generation process to generate clear speech signals.
- ConvNeXt V2F5-TTS improves text representation based on ConvNeXt V2, making it easier to align with speech features and improving the quality and naturalness of speech synthesis.
- Sway Sampling StrategyThe streaming step sampling strategy used during inference improves the model's performance and efficiency based on non-uniform sampling, especially in the early stages of speech generation, which helps the model capture the contours of the target speech more accurately.
- End-to-end system designThe F5-TTS system design is simple and straightforward, from text input to speech output, omitting traditional complex designs such as phoneme alignment and duration prediction, simplifying the model training and inference process.
F5-TTS project address
- GitHub repository:https://github.com/SWivid/F5-TTS
- HuggingFace model library:https://huggingface.co/SWivid/F5-TTS
- arXiv technical paper:https://arxiv.org/pdf/2410.06885
- Experience the demo online:https://huggingface.co/spaces/mrfakename/E2-F5-TTS
Application scenarios of F5-TTS
- audiobooks and podcastsConverting e-books or articles into audiobooks for visually impaired people or users who enjoy listening to audiobooks.
- Voice assistants and chatbotsProvides natural-sounding voice feedback for smart devices and online services, enhancing the user experience.
- Language learning and educationIt helps learners practice pronunciation and listening skills, providing auxiliary tools for language learning.
- News and MediaIt automatically generates audio versions of news reports, providing automated content production for radio stations and online news platforms.
- Customer ServiceUsed in customer service systems to provide automated voice responses and improve the customer experience.