VALL-E is a zero-shot text to speech synthesizer which uses a neural codec language model for text to speech synthesis. It utilizes an off-the-shelf neural audio codec model and leverages existing TTS training data to generate high-quality personalized speech.
The main benefits of VALL-E include:
- Zero-shot synthesis capabilities
- In-context learning capabilities
- High-quality personalized speech generation
- Scaled up TTS training data to 60K hours of English speech
Possible use cases for VALL-E include leveraging the power of GPT text generation for natural language processing applications such as voice recognition, automated customer service, and voice search.
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