tts_transformer-zh-cv7_css10
| Property | Value |
|---|---|
| Author | |
| Research Paper | fairseq S^2 Paper |
| Framework | Fairseq |
| Training Data | Common Voice v7, CSS10 |
What is tts_transformer-zh-cv7_css10?
This is a sophisticated text-to-speech model based on the Transformer architecture, specifically designed for Simplified Chinese language synthesis. Developed by Facebook using the fairseq S^2 framework, it combines pre-training on Common Voice v7 dataset with fine-tuning on CSS10 to deliver high-quality speech synthesis with a single female voice.
Implementation Details
The model leverages the Transformer architecture introduced in the paper "Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition" and is implemented using the fairseq framework. It utilizes HiFiGAN as the vocoder for waveform generation and supports both CPU and GPU inference.
- Transformer-based sequence-to-sequence architecture
- Pre-trained on Common Voice v7 dataset
- Fine-tuned on CSS10 Chinese corpus
- Integrated HiFiGAN vocoder support
Core Capabilities
- High-quality Simplified Chinese speech synthesis
- Single-speaker female voice output
- Support for custom text input
- Easy integration with Python applications
- Flexible audio generation parameters
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized focus on Simplified Chinese text-to-speech synthesis, combining the robust Transformer architecture with high-quality training data from both Common Voice and CSS10 datasets. The use of fairseq S^2 framework ensures reliable performance and easy integration.
Q: What are the recommended use cases?
The model is ideal for applications requiring Simplified Chinese speech synthesis, such as audiobook generation, virtual assistants, educational tools, and accessibility applications. It's particularly suitable for scenarios requiring a natural female voice output.
