Amadeus TTS Model
| Property | Value |
|---|---|
| License | CC-BY-4.0 |
| Framework | ESPnet |
| Language | Japanese |
| Paper | ESPnet: End-to-End Speech Processing Toolkit |
What is amadeus?
Amadeus is a specialized Japanese text-to-speech model developed using the ESPnet framework. Built by developer mio, it implements the VITS (Conditional Variational Autoencoder with Adversarial Learning) architecture for high-quality voice synthesis. The model operates at a 22.05kHz sampling rate and utilizes advanced neural network components for natural speech generation.
Implementation Details
The model employs a sophisticated architecture with multiple key components: a text encoder with 6 transformer blocks, a decoder with multi-scale discriminators, and a stochastic duration predictor. It uses a linear spectrogram as the acoustic feature with a 1024-point FFT and 256-point hop length.
- Hidden channels: 192 with VITS generator architecture
- Text encoder with 2 attention heads and 4x FFN expansion
- Multi-scale discriminator with periods [2,3,5,7,11]
- Decoder with 512 channels and progressive upsampling
Core Capabilities
- Japanese text-to-speech synthesis with accent modeling
- High-fidelity audio generation at 22.05kHz
- Support for pyopenjtalk-based text processing
- Integrated pitch and duration modeling
Frequently Asked Questions
Q: What makes this model unique?
This model combines the powerful VITS architecture with Japanese-specific features like accent modeling and pyopenjtalk integration, making it specifically optimized for Japanese speech synthesis.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality Japanese speech synthesis, such as virtual assistants, audiobook generation, or content localization systems. It's particularly suitable when natural-sounding Japanese speech with proper accent handling is required.
