Metadata-Version: 2.5
Name: antalia-mini
Version: 1.0.1
Summary: Antalia-2 Mini: small Turkish text to speech, one synthetic voice, 7.6M parameters, 48 kHz, faster than real time on a CPU
Project-URL: Homepage, https://huggingface.co/cloud0day3/antalia-mini
Author: PatientDesk AI
License-Expression: Apache-2.0
License-File: LICENSE
License-File: NOTICE
Keywords: flow-matching,speech-synthesis,text-to-speech,tts,turkish
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: Turkish
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Multimedia :: Sound/Audio :: Speech
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Requires-Dist: cmudict>=1.0
Requires-Dist: numpy>=1.24
Requires-Dist: safetensors>=0.4
Requires-Dist: soundfile>=0.12
Requires-Dist: torch>=2.4
Provides-Extra: hub
Requires-Dist: huggingface-hub>=0.23; extra == 'hub'
Provides-Extra: test
Requires-Dist: pytest>=8; extra == 'test'
Requires-Dist: scipy; extra == 'test'
Description-Content-Type: text/markdown

# antalia-mini

Antalia-2 Mini is a small Turkish text-to-speech model with one synthetic voice: 7.6M parameters, 48 kHz
output, well faster than real time on a CPU; code and weights are Apache-2.0. It takes raw Turkish text; numbers, dates,
times, amounts, initialisms, web addresses and English or brand words are normalised inside the package.
The voice is not a real person's, and no recordings of real speakers were used in training.

```bash
pip install antalia-mini
```

```python
from antalia_mini import Antalia

tts = Antalia()  # downloads the weights from Hugging Face once; GPU if available
speech = tts.say("Randevunuz 14 Ekim Salı günü saat 15:30'da.", path="randevu.wav", seed=0)
speech.audio, speech.sample_rate, speech.duration, speech.seed

for chunk in tts.stream("Uzun bir metin. Cümle cümle üretilir."):
    ...  # float32 numpy chunks, first sentence first

tts8k = Antalia(sample_rate=8000)  # 48000 (native), 24000, 16000 or 8000
```

Command line: `antalia-mini "Merhaba." -o merhaba.wav`

Model card, samples, evaluation and limitations: https://huggingface.co/cloud0day3/antalia-mini

Please tell listeners when they are hearing a synthetic voice, and do not use the model to impersonate
real people.
