TEN-framework
/

ten-vad

@@ -19,7 +19,7 @@ The precision-recall curves comparing the performance of WebRTC VAD (pitch-based
 <div style="text-align:">
-  <img src="./images/PR_Curves_TEN-VAD-TestSet.png" width="800">
 </div>
 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. The precision-recall curve can be obtained by executing the following script on Linux x64. The output figure will be saved in the same directory as the script. Note that only PR curves of Silero VAD and TEN VAD are plotted, we did not plot the one of WebRTC VAD, which is used in the latese version of WebRTC.
@@ -33,7 +33,7 @@ python plot_pr_curves.py
 ### **2. Agent-Friendly:**
 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.
 <div style="text-align:">
-  <img src="./images/Agent-Friendly-image.png" width="800">
 </div>
@@ -338,7 +338,7 @@ cd ./examples
     3.2. In Xcode IDE, select ten_vad_demo target (should check: Edit Scheme → Run → Release), then select your iOS Device (not simulator).
     <div style="text-align:">
-      <img src="./images/ios_image_1.jpg" width="800">
     </div>
     3.3. Drag ten_vad/lib/iOS/ten_vad.framework  to "Frameworks, Libraries, and Embedded Content"
@@ -350,7 +350,7 @@ cd ./examples
     - Note: If this step is not completed, you may encounter the following runtime error: "dyld: Library not loaded: @rpath/ten_vad.framework/ten_vad".
       <div style="text-align:">
-        <img src="./images/ios_image_2.png" width="800">
       </div>
     3.4. Configure iOS device Signature

 <div style="text-align:">
+  <img src="./examples/images/PR_Curves_TEN-VAD-TestSet.png" width="800">
 </div>
 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. The precision-recall curve can be obtained by executing the following script on Linux x64. The output figure will be saved in the same directory as the script. Note that only PR curves of Silero VAD and TEN VAD are plotted, we did not plot the one of WebRTC VAD, which is used in the latese version of WebRTC.
 ### **2. Agent-Friendly:**
 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.
 <div style="text-align:">
+  <img src="./examples/images/Agent-Friendly-image.png" width="800">
 </div>
     3.2. In Xcode IDE, select ten_vad_demo target (should check: Edit Scheme → Run → Release), then select your iOS Device (not simulator).
     <div style="text-align:">
+      <img src="./examples/images/ios_image_1.jpg" width="800">
     </div>
     3.3. Drag ten_vad/lib/iOS/ten_vad.framework  to "Frameworks, Libraries, and Embedded Content"
     - Note: If this step is not completed, you may encounter the following runtime error: "dyld: Library not loaded: @rpath/ten_vad.framework/ten_vad".
       <div style="text-align:">
+        <img src="./examples/images/ios_image_2.png" width="800">
       </div>
     3.4. Configure iOS device Signature