Transform text to speech using a reference audio
Enhance and clean audio files
Generate lofi effect for your audio
Generate speech quality score from audio
Use DeepFilterNet2 to denoise audio no file size limit
Process audio to denoise or extract noise
Increase or decrease MP3 volume up to 500%
F5-TTS & E2-TTS: Zero-Shot Voice Cloning (Unofficial Demo)
Versatile audio super resolution (any -> 48kHz) with AudioSR
Versatile audio super resolution (any -> 48kHz) with AudioSR
Optimize audio mastering style using your audio and reference audio
Transcribe audio and rate quality
Enhance speech quality in audio files
GPT-SoVITS Zero-shot TTS Demo is a cutting-edge AI-powered tool designed to transform text into high-quality speech. It leverages advanced voice cloning technology, utilizing a reference audio to generate synthetic speech that closely matches the voice characteristics of the input audio. This tool is particularly useful for creating realistic voice outputs without the need for extensive voice databases or prior training on specific voices.
• Voice Cloning: Generate speech that mimics the voice characteristics of a reference audio. • Zero-Shot TTS: No need for pre-trained voice models; works directly with the provided reference audio. • High-Quality Audio: Produces clear and natural-sounding speech synthesis. • Multilingual Support: Capable of generating speech in multiple languages. • Customizable Settings: Adjust speech rate, pitch, and other parameters for tailored output.
What is the purpose of the reference audio in GPT-SoVITS Zero-shot TTS Demo?
The reference audio is used to clone the voice characteristics of the speaker, allowing the generated speech to sound like the speaker in the reference audio.
Can I use GPT-SoVITS Zero-shot TTS Demo for multiple languages?
Yes, the tool supports multiple languages, making it versatile for different linguistic needs.
Is there a limit to the length of text I can convert to speech?
Yes, there may be limits on the text length, depending on the demo's configuration and available resources. Experiment with shorter texts for optimal performance.