Update README.md

README.md

@@ -27,6 +27,11 @@ tags:
 
 
 *Latest News* 🔥
+- [2025/11] **WASM** build guide and browser test demo are now available in `lib/Web` and `examples`.
+- [2025/11] We supported **Python** inference with **ONNX model** on **Linux**, **macOS** thanks to Guy Nicholson!
+- [2025/11] We supported **Golang** on **Linux**, **macOS** and **Windows** with usage of the prebuilt-libs thanks to hylarucoder!
+- [2025/11] We supported Java on **Linux, macOS, Windows, Android** with usage of the prebuilt-libs thanks to ZhangYang!
+- [2025/07] 🎉 Exciting news! **TEN VAD** is now integrated into **k2-fsa/sherpa-onnx**, thanks to the fantastic work by Fangjun Kuang! You can now achieve more precise speech segment extraction and enjoy an enhanced ASR experience! Refer to the [documentation](https://k2-fsa.github.io/sherpa/onnx/vad/ten-vad.html) and give it a try!
 - [2025/07] We support **Python inference** on **macOS** and **Windows** with usage of the prebuilt-lib!
 - [2025/06] We **finally** released and **open-sourced** the **ONNX** model and the corresponding **preprocessing code**! Now you can deploy **TEN VAD** on **any platform** and **any hardware architecture**!
 - [2025/06] We are excited to announce the release of **WASM+JS** for Web WASM Support. 
@@ -39,10 +44,12 @@ tags:
 - [Introduction](#introduction)
 - [Key Features](#key-features)
   - [High-Performance](#1-high-performance)
+    - [Performance Comparison](#11-performance-comparison)
   - [Agent-Friendly](#2-agent-friendly)
   - [Lightweight](#3-lightweight)
   - [Multiple Programming Languages and Platforms](#4-multiple-programming-languages-and-platforms)
   - [Supported Sampling Rate and Hop Size](#5-supproted-sampling-rate-and-hop-size)
+- [Developers Testimonial](#developers-testimonial)
 - [Installation](#installation)
 - [Quick Start](#quick-start)
   - [Python Usage](#python-usage)
@@ -108,7 +115,11 @@ The precision-recall curves comparing the performance of WebRTC VAD (pitch-based
   <img src="./examples/images/PR_Curves_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 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. 
+
+#### **1.1 Performance Comparison**
+
+Developers can reproduce the performance comparison PR curves for **TEN VAD** and **Silero VAD** on the open-source testset (as shown in the figure above) by executing the following script on Linux x64 with a simply one line of code. The output figure will be saved in the same directory as the script.
 
 ```
 cd ./examples
@@ -202,6 +213,12 @@ TEN VAD provides cross-platform C compatibility across five operating systems (L
 ### **5. Supproted sampling rate and hop size:**
 TEN VAD operates on 16kHz audio input with configurable hop sizes (optimized frame configurations: 160/256 samples=10/16ms). Other sampling rates must be resampled to 16kHz.
 
+## **Developers Testimonial**
+> "We selected TEN VAD because it provides faster and more accurate sentence-end detection in Japanese compared to other VADs, while still being lightweight and fast enough for live use." - LiveCap,Hakase shojo.
+
+> "TEN VAD's overall performance is better than Silero VAD. Its high accuracy and low resource consumption helped us improve efficiency and significantly reduce costs." - Rustpbx.
+
+
 ## **Installation**
 ```
 git clone https://huggingface.co/TEN-framework/ten-vad
@@ -538,7 +555,7 @@ Most questions can be answered by using DeepWiki, it is fast, intutive to use an
 
 ## License
 
-This project is licensed under Apache 2.0 with certain conditions. Refer to the "LICENSE" file in the root directory for detailed information. Note that `pitch_est.cc` contains modified code derived from [LPCNet](https://github.com/xiph/LPCNet), which is [BSD-2-Clause](https://spdx.org/licenses/BSD-2-Clause.html) and [BSD-3-Clause](https://spdx.org/licenses/BSD-3-Clause.html) licensed, refer to the NOTICES file in the root directory for detailed information.
+This project is licensed pursuant to the Apache 2.0 with additional conditions. Refer to the "LICENSE" file in the root directory for detailed information. Note that `pitch_est.cc` contains modified code derived from [LPCNet](https://github.com/xiph/LPCNet), which is [BSD-2-Clause](https://spdx.org/licenses/BSD-2-Clause.html) and [BSD-3-Clause](https://spdx.org/licenses/BSD-3-Clause.html) licensed, refer to the NOTICES file in the root directory for detailed information.