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Piper TTS - Turkish (Cem)

Single-speaker Turkish TTS model (speaker: Cem, 4490 utterances).

Sample rate: 24000 Hz
Phonemes: 256 (espeak-ng/tr)
Speakers: 1 (Cem)
Architecture: Piper custom hybrid (resblock=1, upsample_initial_channel=512)
Inference params: 21.0M
Training: 437 epochs, ~1.77M steps

Available Models

Variant	Size	Type
`last.onnx`	84.9 MB	FP32 (original)
`last.q8.onnx`	30.8 MB	INT8 dynamic quantization (recommended for CPU/RPi)

Q8 (INT8) gives ~64% size reduction with minimal quality loss. Ideal for Raspberry Pi and CPU inference.

Sample Audio

Cem voice reading a Turkish finance/economy paragraph (~24s, 410 chars):

Epoch 426:

Epoch 450~

Inference CPU - intel 14600K - 0.4 avg_rtf

Usage

# With piper CLI
echo "Merhaba dünya" | piper --model last.q8.onnx --output-raw | aplay -r 24000 -f S16_LE -t raw

import onnxruntime as ort
import numpy as np

session = ort.InferenceSession("last.q8.onnx")
dummy = {
    "input": np.random.randint(0, 100, (1, 50), dtype=np.int64),
    "input_lengths": np.array([50], dtype=np.int64),
    "scales": np.array([0.667, 1.0, 0.8], dtype=np.float32),
}
audio = session.run(["output"], dummy)[0]

Or with piper-phonemize + piper-tts.

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