Clone Any Voice in 10 Seconds with AI
Experience F5-TTS, the most realistic open-source zero-shot voice cloning model. Trained on 100,000 hours of multilingual data with 0.15 real-time factor. Support for multiple languages with natural emotion expression and instant voice replication.
Experience zero-shot voice cloning with F5-TTS and E2-TTS
Note: This demo showcases both F5-TTS and E2-TTS models. Upload a 10-second reference audio and input your text to experience instant voice cloning. The demo runs on Hugging Face Spaces and may take a moment to initialize.
F5-TTS represents a breakthrough in zero-shot voice cloning technology, combining advanced AI with natural speech synthesis.
F5-TTS (Fairytaler that Fakes Fluent and Faithful Speech) is a non-autoregressive, zero-shot text-to-speech system built on flow matching and diffusion transformers. It uses a Diffusion Transformer with ConvNeXt V2 architecture for faster training and inference.
Trained on approximately 100,000 hours of multilingual speech data, F5-TTS achieves an impressive real-time factor of 0.15, enabling immediate voice output suitable for live applications. It can clone a voice from just 10 seconds of reference audio without any fine-tuning.
E2-TTS (Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS) uses a Flat-UNet Transformer architecture, representing the closest reproduction from the original paper. It consists of just two main components: a flow-matching-based mel spectrogram generator and a vocoder.
This simplified architecture allows for easier implementation and flexibility while maintaining high-quality voice synthesis. E2-TTS excels at natural prosody and emotion expression, making it ideal for applications requiring expressive speech output.
Explore what makes F5-TTS the most realistic open-source voice cloning solution
Clone any voice from just 10 seconds of reference audio without training or fine-tuning. F5-TTS instantly captures vocal characteristics including tone, pitch, timbre, and speaking style for immediate replication.
Seamlessly synthesize speech in multiple languages including English and Chinese. F5-TTS adapts to deliver clear and natural speech across different languages with the ability to switch languages mid-utterance.
Generate speech with authentic emotional nuances and prosody. F5-TTS captures and reproduces natural speaking patterns, pauses, and emotional inflections from reference audio for highly expressive output.
Achieve faster-than-realtime synthesis with a 0.15 real-time factor. Generate audio faster than playback duration, enabling truly interactive applications like live assistants and real-time voice responses.
Convert e-books into quality audiobooks and support stable processing of long-form content while maintaining voice consistency. Set different character voices to enhance expressiveness across extended narratives.
Fully open-source with permissive licensing allowing commercial use, modification, and distribution. Access complete model weights, training code, and architecture documentation for customization and research.
Built on cutting-edge flow matching and diffusion models
F5-TTS combines transformer models with diffusion models using ConvNeXt V2 blocks for enhanced feature extraction. The flow matching approach enables non-autoregressive generation, producing entire mel spectrograms in parallel rather than sequentially.
This architecture achieves faster training convergence and inference speed compared to traditional autoregressive models. The diffusion process gradually refines noisy spectrograms into high-quality speech representations while maintaining temporal coherence and natural prosody.
F5-TTS was trained on approximately 100,000 hours of multilingual speech data, encompassing diverse speakers, accents, recording conditions, and acoustic environments. This massive scale enables robust zero-shot generalization across unseen voices and languages.
The training corpus includes English, Chinese, and other languages with varying prosodic patterns and phonetic characteristics. This diversity allows the model to capture universal speech patterns while adapting to language-specific features for high-quality synthesis across multiple tongues.
E2-TTS employs a Flat-UNet Transformer architecture with just two main components: a flow-matching mel spectrogram generator and a vocoder. This simplified design allows for easier implementation and modification while maintaining competitive quality.
Users can choose between F5-TTS for maximum performance and speed, or E2-TTS for faithful reproduction of the original paper's architecture. Both models offer zero-shot voice cloning with natural prosody and emotion expression.
Deploy F5-TTS for professional voice cloning applications
Convert e-books into quality audiobooks with consistent narrator voices. Clone voice actors for series continuity, create distinct character voices, and produce long-form content efficiently.
Generate professional voiceovers for videos, podcasts, and presentations. Clone presenter voices for consistency across episodes or create custom voice personas for branding.
Localize content while preserving original voice characteristics. Clone actors' voices across languages for authentic dubbed versions without expensive recording sessions.
Build custom voice personalities for AI assistants and conversational interfaces. Create unique brand voices or clone company spokespersons for consistent customer interactions.
Generate dynamic NPC dialogue and character voices for games. Create procedural voice content that adapts to gameplay while maintaining character consistency.
Build screen readers and assistive communication devices with natural voice output. Create personalized voices for individuals with speech disabilities.
Produce educational content with consistent instructor voices across multilingual platforms. Create personalized learning experiences with custom voice narration.
Design natural-sounding interactive voice response systems. Clone company spokesperson voices for brand consistency in automated customer interactions.
Clone podcast host voices for editing corrections, create intro/outro segments, or generate voice content when recording isn't feasible.
Clone your first voice in minutes with the Python API
Install F5-TTS from GitHub. Requires Python 3.9+ and PyTorch.
git clone https://github.com/SWivid/F5-TTS.git
cd F5-TTS
pip install -e .
Use F5-TTS to clone any voice from reference audio:
from f5_tts.api import F5TTS
tts = F5TTS()
# Clone voice and synthesize
audio = tts.synthesize(
text="Your text here",
ref_audio="reference.wav",
ref_text="Reference transcript"
)
# Save output
audio.save("output.wav")
Select between F5-TTS and E2-TTS based on your needs:
# Use F5-TTS (faster, ConvNeXt V2)
tts = F5TTS(model="F5-TTS")
# Use E2-TTS (original architecture)
tts = F5TTS(model="E2-TTS")
# Adjust generation parameters
audio = tts.synthesize(
text="Your text",
ref_audio="reference.wav",
speed=1.0,
cross_fade_duration=0.15
)
Common questions about F5-TTS and voice cloning
F5-TTS can clone a voice from as little as 10 seconds of clear reference audio. For best results, use 10-30 seconds of clean speech with minimal background noise. The reference audio should contain natural speech patterns and represent the speaker's typical vocal characteristics.
Longer reference samples (30+ seconds) can improve consistency for extended synthesis, but F5-TTS's zero-shot capability means you don't need extensive training data like traditional voice cloning methods require.
F5-TTS uses a Diffusion Transformer with ConvNeXt V2, offering faster training and inference with a 0.15 real-time factor. It's optimized for speed and production deployment.E2-TTS uses a Flat-UNet Transformer architecture, closely following the original paper with simpler implementation.
Choose F5-TTS for maximum performance and real-time applications. ChooseE2-TTS for research purposes or if you need the original architecture. Both models deliver comparable voice cloning quality.
F5-TTS officially supports multiple languages including English and Chinese with high quality. The model was trained on approximately 100,000 hours of multilingual speech data, enabling it to handle various languages and accents.
The zero-shot architecture means F5-TTS can potentially work with other languages present in its training data, though quality may vary. The model can also handle code-switching, allowing seamless language transitions within the same utterance.
Yes, F5-TTS is fully open-source with permissive licensing that allows commercial use. You can use F5-TTS in commercial products, integrate it into SaaS platforms, or deploy it in production environments without licensing fees or usage restrictions.
The open-source nature means you have access to complete model weights, training code, and architecture details for customization. However, ensure you have proper rights to any reference audio used for voice cloning, as voice rights and consent remain important legal considerations.
F5-TTS requires a GPU for real-time inference. A consumer GPU with at least 8GB VRAM (such as NVIDIA RTX 3060 or higher) is recommended for smooth operation. For faster-than-realtime performance with the 0.15 real-time factor, a more powerful GPU like RTX 4090 is ideal.
CPU-only inference is possible but significantly slower and not suitable for real-time applications. For production deployments requiring high throughput, consider using dedicated GPU servers or cloud GPU instances with sufficient VRAM and compute capability.
Experience the most realistic open-source zero-shot voice cloning with F5-TTS. Clone voices in 10 seconds with natural emotion and multi-language support.
Open-Source • 100K+ Training Hours • 0.15x Real-Time • Multi-Language Support