Kokoro-82M

license: apache-2.0 language:

• en base_model:
• yl4579/StyleTTS2-LJSpeech pipeline_tag: text-to-speech

🐈 GitHub: https://github.com/hexgrad/kokoro 🚀 Demo: https://hf.co/spaces/hexgrad/Kokoro-TTS

Kokoro

Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.

Releases

Usage

You can run this basic cell on Google Colab. Listen to samples. For more languages and details, see Advanced Usage.

!pip install -q kokoro>=0.9.2 soundfile
!apt-get -qq -y install espeak-ng > /dev/null 2>&1

from kokoro import KPipeline
from IPython.display import display, Audio
import soundfile as sf
import torch

pipeline = KPipeline(lang_code='a')

text = '''
[Kokoro](/kˈOkəɹO/) is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, [Kokoro](/kˈOkəɹO/) can be deployed anywhere from production environments to personal projects.
'''

generator = pipeline(text, voice='af_heart')
for i, (gs, ps, audio) in enumerate(generator):
    print(i, gs, ps)
    display(Audio(data=audio, rate=24000, autoplay=i==0))
    sf.write(f'{i}.wav', audio, 24000)

Under the hood, kokoro uses misaki, a G2P library at https://github.com/hexgrad/misaki

Model Facts

Architecture:

• StyleTTS 2: https://arxiv.org/abs/2306.07691
• ISTFTNet: https://arxiv.org/abs/2203.02395
• Decoder only: no diffusion, no encoder release
• Architected by: Li et al @ https://github.com/yl4579/StyleTTS2

Trained by: @rzvzn on Discord Languages: Multiple Model SHA256 Hash: 496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4

Training Details

Data: Kokoro was trained exclusively on permissive/non-copyrighted audio data and IPA phoneme labels. Examples of permissive/non-copyrighted audio include:

• Public domain audio
• Audio licensed under Apache, MIT, etc.
• Synthetic audio[1] generated by closed[2] TTS models from large providers

[1] https://copyright.gov/ai/ai_policy_guidance.pdf [2] No synthetic audio from open TTS models or "custom voice clones"

Total Dataset Size: A few hundred hours of audio Total Training Cost: About $1000 for 1000 hours of A100 80GB vRAM

Creative Commons Attribution

The following CC BY audio was part of the dataset used to train Kokoro v1.0.