French-Tortoise
| Property | Value |
|---|---|
| Author | Snowad |
| License | Apache-2.0 |
| Language | French |
| Pipeline | Text-to-Speech |
What is French-Tortoise?
French-Tortoise is a specialized text-to-speech model that builds upon the Tortoise-TTS framework, specifically optimized for French language synthesis. The model has evolved through multiple versions, with the latest V2.5 representing a significant advancement in French speech generation capabilities.
Implementation Details
The model's development progressed through three major versions, each with distinct training characteristics: V2.5 was fine-tuned on 517k CommonVoice samples for 2.5k steps, V2 utilized 120k samples from multiple sources (SIWIS, Common Voice, M-AILABS) trained for 10k steps on an RTX 3090, and V1 was trained on 24k samples for 8850 steps.
- Training Infrastructure: RTX 3090 GPU
- Training Duration: Approximately 21 hours for V2
- Dataset Composition: Multiple high-quality French speech datasets
Core Capabilities
- Natural French pronunciation without English accent
- Multi-speaker support
- Voice cloning functionality (better results with fine-tuning)
- Compatible with optimized Tortoise-TTS forks
Frequently Asked Questions
Q: What makes this model unique?
The model's primary strength lies in its ability to generate French speech without the typical English accent found in base Tortoise models, achieved through extensive fine-tuning on French-specific datasets.
Q: What are the recommended use cases?
The model is ideal for French text-to-speech applications, particularly when natural pronunciation is crucial. For voice cloning applications, it's recommended to fine-tune the model on specific voice datasets for optimal results.
