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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - he
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+ tags:
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+ - text-to-speech
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+ - tts
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+ - hebrew
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+ - audio
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+ - fast-inference
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+ license: mit
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+ datasets:
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+ - notmax123/RanLevi40h
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+ ---
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+
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+ # LightBlue TTS 馃嚠馃嚤
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+
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+ ## Model Description
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+
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+ LightBlue is a state-of-the-art, lightning-fast Text-to-Speech (TTS) model built from scratch specifically for Hebrew (with English support). It is designed to produce 100% native Israeli-sounding speech with perfect handling of *Nikud* (vowels) and complex homographs, without compromising on inference speed.
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+
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+ It is fast enough to generate an entire 1-hour audiobook in just **3 seconds** on a modern GPU.
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+
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+ - **Developer:** LightBlue TTS
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+ - **Language(s):** Hebrew (Primary), English
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+ - **Model Type:** Text-to-Speech (TTS)
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+ - **Demo & Website:** [https://lightbluetts.com/](https://lightbluetts.com/)
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+
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+ ## Key Features
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+
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+ - **Blazing Fast Inference:**
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+ - **1260x real-time** on an NVIDIA RTX 3090 (21 minutes of audio generated per second).
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+ - **35x real-time** on standard CPUs.
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+ - **20x real-time** on Apple M1 chips.
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+ - **Native Hebrew Quality:** Features a real Israeli accent, correct stress placements, and native-level flow.
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+ - **Advanced Contextual Understanding:** Passes the "Homograph Test" (e.g., correctly distinguishing between *爪驻讛* as "watched" vs "floated", or *转专讚* as "spinach" vs "go down").
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+ - **Multiple Voices:** Includes high-quality voices like *Yonatan* (Hebrew only) and *Rotem*.
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+
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+ ## Uses
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+
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+ ### Direct Use
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+ - Generating high-quality Hebrew audio from text.
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+ - Real-time TTS applications running on standard CPUs or edge devices.
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+ - Audiobooks, accessibility tools, virtual assistants, and automated broadcasting.
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+
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+ ## Speed Benchmarks
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+
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+ LightBlue is optimized for extreme speed without sacrificing naturalness:
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+
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+ | Hardware | Speed | Time for 1 Hour of Audio |
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+ | :--- | :--- | :--- |
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+ | **NVIDIA RTX 3090** | 1260x real-time | ~3 seconds |
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+ | **Standard CPU** | 35x real-time | ~1.7 minutes |
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+ | **Apple M1** | 20x real-time | ~3 minutes |
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+
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+ ## How to Get Started
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+
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+ *(Note: Replace with the actual inference code depending on how the model weights are loaded.)*
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+
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+ ```python
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+ # Example pseudo-code for inference
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+ from lightblue import LightBlueTTS
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+
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+ # Load the model
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+ tts = LightBlueTTS.from_pretrained("lightblue-tts/hebrew")
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+
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+ # Generate speech
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+ text = "讗转诪讜诇 讞讝专转讬 诪讗讜讞专 讛讘讬转讛 讜讙讬诇讬转讬 砖砖讻讞转讬 讗转 讛诪驻转讞讜转 讘诪砖专讚."
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+ audio = tts.synthesize(text, voice="yonatan")
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+
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+ # Save to file
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+ audio.save("output.wav")