• Lightweight and compact, suitable for edge devices with limited computational resources.• Balances expressive prosody with low latency, ensuring natural-sounding speech in real-time voice synthesis.• Incorporates multi-speaker conditioning and a refined acoustic tokenizer to adapt to diverse linguistic styles.
| Metric | Qwen3-TTS-12Hz-1.7B-Base Model |
|---|---|
| Parameters | 1.7B |
| Update Rate | 12 Hz |
| MOS (Mean Opinion Score) | 4.6 |
| Latency | < 100 ms |
| Memory Footprint | ≈ 800 MB |
• Real-time voice synthesis with natural-sounding speech and expressive prosody.• Superior latency and quality metrics compared to similar models.• Adapts to diverse linguistic styles through multi-speaker conditioning and refined acoustic tokenizer.
• Compact architecture with low computational overhead.• Suitable for edge devices and real-time voice synthesis applications.• Incorporates advanced techniques to produce high-quality, natural-sounding speech.
• Reduced latency and improved quality in real-time voice synthesis applications.• Enhanced adaptability to diverse linguistic styles through multi-speaker conditioning.• Increased efficiency and reduced computational overhead due to compact architecture.
| Metric | Qwen3-TTS-12Hz-1.7B-Base Model | Similar Model 1 |
|---|---|---|
| MOS (Mean Opinion Score) | 4.6 | 4.2 |
| Latency | < 100 ms | 150 ms |
| Multispaker Conditioning | N/A | 85% |
Q: What is the update rate of the Qwen3-TTS-12Hz-1.7B-Base Model?A: The model operates at a 12 Hz update rate for real-time voice synthesis.Q: How does the model perform in diverse linguistic styles?A: The model incorporates multi-speaker conditioning and a refined acoustic tokenizer to adapt to various linguistic styles.Q: What is the memory footprint of the model?A: The model has an approximate memory footprint of ≈ 800 MB, making it suitable for edge devices.
