Generate speech from text with reference audio
Convert spoken words to text
Generate text and audio responses to user queries
CPU powered, low RTF, emotional, multilingual TTS
Talk to Qwen2Audio with Gradio and WebRTC ⚡️
Generate high-quality speech from text with specified emotion and voice
Generate audio from text or modify voice pitch
Ebook2audiobook docker space beta
Generate speech from text with customizable voices
Listen and respond to voice commands in Spanish
StyleTTS2 trained on ukrainian dataset
Belarusian TTS
Generate realistic-sounding AI voice from text
GPT SoVITS V2 is an advanced speech synthesis tool powered by GPT technology, designed to generate high-quality speech from text. It leverages reference audio to synthesize natural-sounding voices, making it ideal for voice cloning, audio content creation, and voiceovers. This model is fine-tuned for high-fidelity voice synthesis, offering a responsive and user-friendly interface for generating realistic speech outputs.
• Reference Audio Support: Utilizes reference audio to maintain voice consistency and style.
• Voice Cloning: Capable of mimicking the tone, pitch, and speaking style of the reference speaker.
• Multilingual Support: Generates speech in multiple languages, catering to diverse user needs.
• High-Quality Output: Produces clean and natural-sounding audio with minimal artifacts.
• Customizable Settings: Allows users to adjust parameters for fine-tuning the output to their preferences.
1. What formats are supported for reference audio?
GPT SoVITS V2 supports common audio formats such as MP3, WAV, and FLAC.
2. Can I use GPT SoVITS V2 for commercial purposes?
Yes, GPT SoVITS V2 can be used for commercial purposes, but ensure compliance with applicable laws and regulations regarding voice synthesis and usage rights.
3. How do I achieve the best results with GPT SoVITS V2?
For the best results, use high-quality reference audio and ensure the input text is clear and well-formatted. Adjusting the voice parameters carefully can also enhance the output quality.