KaniTTS EXPO2025 Osaka japanese
A high-speed, high-fidelity Text-to-Speech model optimized for real-time conversational AI applications.
ใใใฎใก่ผใๆชๆฅ็คพไผใฎใใถใคใณใใจใใๅคง้ชใป้ข่ฅฟไธๅ2025ใฎใใผใใ็ฅใใใญใซใฎในใฎไบบใ ใใๆฅๆฌใฎ็ใใพใธ --ๅฟใจๅฟ ใใคใชใ่ดใ็ฉใจใใฆใใฉใใใๅใๅใ ใใ ใใใ
In honor of Expo Osaka 2025 and its motto 'Designing Future Society for Our Lives,' we humbly present this gift from the people of the Kyrgyz Republic to the people of Japan - heart to heart.
Overview
KaniTTS uses a two-stage pipeline combining a large language model with an efficient audio codec for exceptional speed and audio quality. The architecture generates compressed token representations through a backbone LLM, then rapidly synthesizes waveforms via neural audio codec, achieving extremely low latency.
Key Specifications:
- Model Size: 370M parameters
- Sample Rate: 22kHz
- Languages: Japanese
- License: Apache 2.0
Quickstart: Install from PyPI & Run Inference
Itโs a lightweight so you can install, load a model, and speak in minutes. Designed for quick starts and simple workflowsโno heavy setup, just pip install and run. More detailes...
Install
pip install kani-tts
pip install -U "transformers==4.57.1" # for LFM2 !!!
Quick Start
from kani_tts import KaniTTS
model = KaniTTS('nineninesix/kani-tts-370m-expo2025-osaka-ja')
# Generate audio from text
audio, text = model("Your text here")
# Save to file (requires soundfile)
model.save_audio(audio, "output.wav")
Custom Configuration
from kani_tts import KaniTTS
model = KaniTTS(
'nineninesix/kani-tts-370m-expo2025-osaka-ja',
temperature=0.7, # Control randomness (default: 1.0)
top_p=0.9, # Nucleus sampling (default: 0.95)
max_new_tokens=2000, # Max audio length (default: 1200)
repetition_penalty=1.2, # Prevent repetition (default: 1.1)
suppress_logs=True, # Suppress library logs (default: True)
show_info=True, # Show model info on init (default: True)
)
audio, text = model("Your text here")
Playing Audio in Jupyter Notebooks
You can listen to generated audio directly in Jupyter notebooks or IPython:
from kani_tts import KaniTTS
from IPython.display import Audio as aplay
model = KaniTTS('nineninesix/kani-tts-370m-expo2025-osaka-ja')
audio, text = model("Your text here")
# Play audio in notebook
aplay(audio, rate=model.sample_rate)
Performance
Nvidia RTX 5090 Benchmarks:
- Latency: ~1 second to generate 15 seconds of audio
- Memory: 2GB GPU VRAM
- Quality Metrics: MOS 4.3/5 (naturalness), WER <5% (accuracy)
Pretraining:
- Dataset: ~80k hours from LibriTTS, Common Voice, and Emilia
- Hardware: 8x H100 GPUs, 45 hours training time on Lambda AI
Voices Datasets
Audio Examples
| Text | Audio |
|---|---|
| ใใใซใกใฏ๏ผใซใใจ็ณใใพใใ็งใฏใใคในใขใใซใงใ๏ผไฝใซใคใใฆใ่ฉฑใใใพใใใใ๏ผ | |
| 2025ๅนดใฎๅคง้ชใป้ข่ฅฟไธๅใฏ็ด ๆดใใใใคใใณใใงใใใ | |
| ใใใฎใก่ผใๆชๆฅ็คพไผใฎใใถใคใณใใจใใใใผใใๅคใใฎไบบใฎๅฟใซๆฎใใพใใใ | |
| ไธ็ไธญใฎๅฝใ ใๆชๆฅใฎๆ่กใ็ดนไปใใพใใใ | |
| ๅฐใใชไธๆญฉใงใใๅใซ้ฒใใฐๆฏ่ฒใๅคใใใพใใ | |
| ไฝๆฐใชใๆฅๅธธใฎไธญใซใใๅฟใๆธฉใพใ็ฌ้ใใใใพใใ |
Use Cases
- Conversational AI: Real-time speech for chatbots and virtual assistants
- Edge/Server Deployment: Resource-efficient inference on affordable hardware
- Accessibility: Screen readers and language learning applications
- Research: Fine-tuning for specific voices, accents, or emotions
Limitations
- Performance degrades with inputs exceeding 2000 tokens
- Limited expressivity without fine-tuning for specific emotions
- May inherit biases from training data in prosody or pronunciation
Optimization Tips
- Multilingual Performance: Continually pretrain on target language datasets and fine-tune NanoCodec
- Batch Processing: Use batches of 8-16 for high-throughput scenarios
- Hardware: Optimized for NVIDIA Blackwell architecture GPUs
Resources
Models:
Examples:
Links:
Acknowledgments
Built on top of LiquidAI LFM2 350M as the backbone and Nvidia NanoCodec for audio processing.
Responsible Use
Prohibited activities include:
- Illegal content or harmful, threatening, defamatory, or obscene material
- Hate speech, harassment, or incitement of violence
- Generating false or misleading information
- Impersonating individuals without consent
- Malicious activities such as spamming, phishing, or fraud
By using this model, you agree to comply with these restrictions and all applicable laws.
Contact
Have a question, feedback, or need support? Please fill out our contact form and we'll get back to you as soon as possible.
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