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README.md

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@@ -111,9 +111,7 @@ The precision-recall curves comparing the performance of WebRTC VAD (pitch-based
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<br>
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<div style="text-align:">
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<img src="./examples/images/PR_Curves_testset.png" width="800">
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![PR Curves Performance Comparison](https://github.com/TEN-framework/ten-vad/raw/main/examples/images/PR_Curves_testset.png)
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Note that the default threshold of 0.5 is used to generate binary speech indicators (0 for non-speech signal, 1 for speech signal). This threshold needs to be tuned according to your domain-specific task.
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As illustrated in the figure below, TEN VAD rapidly detects speech-to-non-speech transitions, whereas Silero VAD suffers from a delay of several hundred milliseconds, resulting in increased end-to-end latency in human-agent interaction systems. In addition, as demonstrated in the 6.5s-7.0s audio segment, Silero VAD fails to identify short silent durations between adjacent speech segments.
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<img src="./examples/images/Agent-Friendly-image.png" width="800">
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![Agent-Friendly Response](https://github.com/TEN-framework/ten-vad/raw/main/examples/images/Agent-Friendly-image.png)
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<br>
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### **3. Lightweight:**
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3.2. In Xcode IDE, select ten_vad_demo target (should check: Edit Scheme → Run → Release), then select your iOS Device (not simulator).
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<img src="./examples/images/ios_image_1.jpg" width="800">
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![iOS Setup Image 1](https://github.com/TEN-framework/ten-vad/raw/main/examples/images/ios_image_1.jpg)
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3.3. Drag ten_vad/lib/iOS/ten_vad.framework to "Frameworks, Libraries, and Embedded Content"
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- Note: If this step is not completed, you may encounter the following runtime error: "dyld: Library not loaded: @rpath/ten_vad.framework/ten_vad".
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<div style="text-align:">
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<img src="./examples/images/ios_image_2.png" width="800">
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</div>
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![iOS Setup Image 2](https://github.com/TEN-framework/ten-vad/raw/main/examples/images/ios_image_2.png)
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3.4. Configure iOS device Signature
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setup.py

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setup(
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name="ten_vad",
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version="1.0.6.7",
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version="1.0.6.8",
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description="Voice Activity Detector (VAD) : low-latency, high-performance and lightweight",
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packages=["ten_vad"],
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package_data={

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