SpeechT5 TTS
| Property | Value |
|---|---|
| License | MIT |
| Paper | View Paper |
| Downloads | 135,863 |
| Author | Microsoft |
What is speecht5_tts?
SpeechT5 TTS is a sophisticated text-to-speech model that builds upon the success of T5 (Text-To-Text Transfer Transformer) architecture. It implements a unified-modal framework featuring a shared encoder-decoder network and modal-specific pre/post-nets for handling both speech and text data. The model has been fine-tuned specifically for speech synthesis on the LibriTTS dataset.
Implementation Details
The model architecture consists of a shared encoder-decoder network that processes input through pre-nets, performs sequence-to-sequence transformation, and generates output through post-nets. It uses cross-modal vector quantization to align textual and speech information into a unified semantic space.
- Supports 16kHz audio generation
- Utilizes speaker embeddings for voice characteristics
- Implements HifiGAN vocoder for high-quality speech synthesis
- Compatible with 🤗 Transformers library
Core Capabilities
- Text-to-speech synthesis
- Voice conversion
- Speaker adaptation through x-vectors
- High-quality speech generation
- Support for custom voice characteristics
Frequently Asked Questions
Q: What makes this model unique?
SpeechT5 TTS stands out for its unified-modal approach that handles both speech and text in the same framework, allowing for better representation learning and transfer between modalities. Its architecture is inspired by the successful T5 model, adapted specifically for speech processing tasks.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality text-to-speech conversion, including audiobook generation, virtual assistants, accessibility tools, and content localization. It's particularly useful when custom voice characteristics are needed through speaker embeddings.
