KazakhTTS-OmniVoice is a Kazakh text-to-speech model fine-tuned from k2-fsa/OmniVoice.
The model is designed for natural Kazakh speech synthesis and supports controllable voice attributes through OmniVoice's voice design interface, including gender, age-style prompts, and pitch-style prompts.
This checkpoint was fine-tuned specifically for the Kazakh language using a mixture of real Kazakh TTS data and synthetic controlled voice-design data.
KazakhTTS-OmniVoice was fine-tuned using a mixture of real Kazakh speech data and synthetic controlled voice-design data.
The main real speech component comes from ISSAI_KazakhTTS2, a Kazakh text-to-speech dataset used to improve pronunciation, rhythm, and naturalness for Kazakh speech synthesis.
The synthetic component was generated to improve controllability for speaker attributes such as gender, age-style prompts, and pitch-style prompts.
Approximate fine-tuning mixture:
Synthetic controlled dataset:
The synthetic data was generated using a small number of stable reference voices per category, with many Kazakh target texts per voice. This was done to reduce speaker memorization while preserving consistent control behavior.
The original KazakhTTS2 dataset is not included in this repository. This repository only contains the fine-tuned model checkpoint and example audio generated by the model.
Text:
Мен қазақша дауыс моделін тексеріп жатырмын.
Text:
Қайырлы күн! Бүгін біз қазақ тіліндегі мәтінді дыбыстау сапасын тексеріп жатырмыз.
Text:
Сәлеметсіз бе! Сіздің өтінішіңіз қабылданды. Біздің маман сізге жақын арада хабарласады.
Text:
Сәлем! Мен қазақша сөйлей аламын.
Text:
Қазақстанда жасанды интеллект пен сөйлеу технологиялары қарқынды дамып келеді.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
This model is an OmniVoice checkpoint and should be used with the omnivoice Python library.
Install dependencies:
pip install omnivoice soundfile torch
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"shyngys879/KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
text = "Бүгін біз жаңа қазақша дауыс моделін тексеріп жатырмыз. Дауыс табиғи, анық және түсінікті болуы керек."
audio = model.generate(
text=text,
language="Kazakh",
)
sf.write("kazakh_tts_output.wav", audio[0], 24000)
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"shyngys879/KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
audio = model.generate(
text="Бүгін біз қазақша дауыс синтезін тексеріп жатырмыз.",
language="Kazakh",
ref_audio="reference.wav",
ref_text="Бұл reference аудиода айтылған мәтін.",
)
sf.write("kazakh_cloned_voice.wav", audio[0], 24000)
from huggingface_hub import snapshot_download
model_dir = snapshot_download(
repo_id="shyngys879/KazakhTTS-OmniVoice",
local_dir="KazakhTTS-OmniVoice",
)
print(model_dir)
Then load from the local folder:
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
audio = model.generate(
text="Сәлем! Бұл қазақша мәтінді дыбыстау мысалы.",
language="Kazakh",
)
sf.write("out.wav", audio[0], 24000)
The model was trained with the following controllable voice attributes:
For commercial deployment, research collaboration on your organization's data, please contact:
Shyngys Sovetkhan
Email: shyngyssovetkhan0@gmail.com
If your company or organization uses this model, has evaluated it, or has found it useful, I would greatly appreciate a brief official confirmation letter describing the use case or evaluation results. Such documentation helps demonstrate the model's real-world impact in my university applications. The letter can be sent to the email address above.
KazakhTTS-OmniVoice is a Kazakh text-to-speech model fine-tuned from k2-fsa/OmniVoice.
The model is designed for natural Kazakh speech synthesis and supports controllable voice attributes through OmniVoice's voice design interface, including gender, age-style prompts, and pitch-style prompts.
This checkpoint was fine-tuned specifically for the Kazakh language using a mixture of real Kazakh TTS data and synthetic controlled voice-design data.
KazakhTTS-OmniVoice was fine-tuned using a mixture of real Kazakh speech data and synthetic controlled voice-design data.
The main real speech component comes from ISSAI_KazakhTTS2, a Kazakh text-to-speech dataset used to improve pronunciation, rhythm, and naturalness for Kazakh speech synthesis.
The synthetic component was generated to improve controllability for speaker attributes such as gender, age-style prompts, and pitch-style prompts.
Approximate fine-tuning mixture:
Synthetic controlled dataset:
The synthetic data was generated using a small number of stable reference voices per category, with many Kazakh target texts per voice. This was done to reduce speaker memorization while preserving consistent control behavior.
The original KazakhTTS2 dataset is not included in this repository. This repository only contains the fine-tuned model checkpoint and example audio generated by the model.
Text:
Мен қазақша дауыс моделін тексеріп жатырмын.
Text:
Қайырлы күн! Бүгін біз қазақ тіліндегі мәтінді дыбыстау сапасын тексеріп жатырмыз.
Text:
Сәлеметсіз бе! Сіздің өтінішіңіз қабылданды. Біздің маман сізге жақын арада хабарласады.
Text:
Сәлем! Мен қазақша сөйлей аламын.
Text:
Қазақстанда жасанды интеллект пен сөйлеу технологиялары қарқынды дамып келеді.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
Text:
Бұл қазақша мәтінді дыбыстау мысалы.
This model is an OmniVoice checkpoint and should be used with the omnivoice Python library.
Install dependencies:
pip install omnivoice soundfile torch
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"shyngys879/KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
text = "Бүгін біз жаңа қазақша дауыс моделін тексеріп жатырмыз. Дауыс табиғи, анық және түсінікті болуы керек."
audio = model.generate(
text=text,
language="Kazakh",
)
sf.write("kazakh_tts_output.wav", audio[0], 24000)
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"shyngys879/KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
audio = model.generate(
text="Бүгін біз қазақша дауыс синтезін тексеріп жатырмыз.",
language="Kazakh",
ref_audio="reference.wav",
ref_text="Бұл reference аудиода айтылған мәтін.",
)
sf.write("kazakh_cloned_voice.wav", audio[0], 24000)
from huggingface_hub import snapshot_download
model_dir = snapshot_download(
repo_id="shyngys879/KazakhTTS-OmniVoice",
local_dir="KazakhTTS-OmniVoice",
)
print(model_dir)
Then load from the local folder:
from omnivoice import OmniVoice
import soundfile as sf
import torch
model = OmniVoice.from_pretrained(
"KazakhTTS-OmniVoice",
device_map="cuda:0",
dtype=torch.float16,
)
audio = model.generate(
text="Сәлем! Бұл қазақша мәтінді дыбыстау мысалы.",
language="Kazakh",
)
sf.write("out.wav", audio[0], 24000)
The model was trained with the following controllable voice attributes:
For commercial deployment, research collaboration on your organization's data, please contact:
Shyngys Sovetkhan
Email: shyngyssovetkhan0@gmail.com
If your company or organization uses this model, has evaluated it, or has found it useful, I would greatly appreciate a brief official confirmation letter describing the use case or evaluation results. Such documentation helps demonstrate the model's real-world impact in my university applications. The letter can be sent to the email address above.