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README.md CHANGED
@@ -22,6 +22,8 @@ pipeline_tag: audio-to-audio
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  > **8 MB model · Runs fully on CPU in real time · Trained on 10,000+ hours of mixed audio · Under 1 ms processing per 10 ms of audio**
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  [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/pulp-vision/Hush)
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  [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
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  [![Python](https://img.shields.io/badge/python-3.9%2B-blue.svg)](https://python.org)
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  ---
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  ## Model Overview
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  Hush is designed from the ground up for **Voice AI applications** — phone-based voice agents, call centre bots, voice assistants, real-time transcription pipelines, and conversational AI systems. It isolates exactly one speaker from a live audio stream, in real time, under production conditions.
 
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  > **8 MB model · Runs fully on CPU in real time · Trained on 10,000+ hours of mixed audio · Under 1 ms processing per 10 ms of audio**
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+ > 🚀 **Coming Soon:** We are currently fine-tuning a new model optimized specifically for environments with even **louder background noise and louder background speech**! Stay tuned for the upcoming release.
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+
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  [![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/pulp-vision/Hush)
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  [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
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  [![Python](https://img.shields.io/badge/python-3.9%2B-blue.svg)](https://python.org)
 
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  ---
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+ ## Listen to the Model (Use headphones)
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+
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+ **Raw Audio (Noisy Environment):**
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+
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+ <audio controls src="https://huggingface.co/weya-ai/hush/resolve/main/assets/audio/sample_00006_raw.wav"></audio>
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+
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+ **Denoised Audio (Hush Output):**
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+
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+ <audio controls src="https://huggingface.co/weya-ai/hush/resolve/main/assets/audio/sample_00006_denoised.wav"></audio>
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+
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+ ---
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+
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  ## Model Overview
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  Hush is designed from the ground up for **Voice AI applications** — phone-based voice agents, call centre bots, voice assistants, real-time transcription pipelines, and conversational AI systems. It isolates exactly one speaker from a live audio stream, in real time, under production conditions.
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