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ema-lightning

canberkkkkkk

**Tiny, fast and accurate Turkish text to speech.** A 5.6M-parameter DiT acoustic model and a 3M-parameter vocoder: 8.6M in total, about 34 MB. Apache 2.0. - **Most accurate on Freya-TR-Eval:** 0.92% WER, the lowest of every system measured, including ElevenLabs v4, Gemini 3.8 and the 2.38B-parameter Trendyol-TTS. - **Fast:** first audio in 3.86 ms and 440× faster than real time on an RTX 4090; 1,316× with batching. - **Streams:** audio starts while the rest of the text is still being generated. - **Cheap:** about $0.0085 per million characters on a rented RTX 4090. - **Runs anywhere:** GPU or CPU, fully offline. No API key, and no text or audio leaves the machine. - **One model serves many callers:** call it from as many threads as you like; its scheduler, Playhead, runs everyone's work together on the GPU. - **Code:** [EMA Lightning on GitHub][github] - **Package:** `pip install ema-lightning` - **Text frontend:** normalizer-tr, by Erdem Tuna

Speech synthesis

Input Text→ Output Audio

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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ema-lightning

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