diff --git a/examples/java-example/pom.xml b/examples/java-example/pom.xml
new file mode 100644
index 0000000..32ba720
--- /dev/null
+++ b/examples/java-example/pom.xml
@@ -0,0 +1,30 @@
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+
+  <groupId>org.example</groupId>
+  <artifactId>java-example</artifactId>
+  <version>1.0-SNAPSHOT</version>
+  <packaging>jar</packaging>
+
+  <name>sliero-vad-example</name>
+  <url>http://maven.apache.org</url>
+
+  <properties>
+    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>junit</groupId>
+      <artifactId>junit</artifactId>
+      <version>3.8.1</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.microsoft.onnxruntime</groupId>
+      <artifactId>onnxruntime</artifactId>
+      <version>1.16.0-rc1</version>
+    </dependency>
+  </dependencies>
+</project>
diff --git a/examples/java-example/src/main/java/org/example/App.java b/examples/java-example/src/main/java/org/example/App.java
new file mode 100644
index 0000000..7b58f17
--- /dev/null
+++ b/examples/java-example/src/main/java/org/example/App.java
@@ -0,0 +1,69 @@
+package org.example;
+
+import ai.onnxruntime.OrtException;
+import javax.sound.sampled.*;
+import java.util.Map;
+
+public class App {
+
+    private static final String MODEL_PATH = "src/main/resources/silero_vad.onnx";
+    private static final int SAMPLE_RATE = 16000;
+    private static final float START_THRESHOLD = 0.6f;
+    private static final float END_THRESHOLD = 0.45f;
+    private static final int MIN_SILENCE_DURATION_MS = 600;
+    private static final int SPEECH_PAD_MS = 500;
+    private static final int WINDOW_SIZE_SAMPLES = 2048;
+
+    public static void main(String[] args) {
+        // Initialize the Voice Activity Detector
+        SlieroVadDetector vadDetector;
+        try {
+            vadDetector = new SlieroVadDetector(MODEL_PATH, START_THRESHOLD, END_THRESHOLD, SAMPLE_RATE, MIN_SILENCE_DURATION_MS, SPEECH_PAD_MS);
+        } catch (OrtException e) {
+            System.err.println("Error initializing the VAD detector: " + e.getMessage());
+            return;
+        }
+
+        // Set audio format
+        AudioFormat format = new AudioFormat(SAMPLE_RATE, 16, 1, true, false);
+        DataLine.Info info = new DataLine.Info(TargetDataLine.class, format);
+
+        // Get the target data line and open it with the specified format
+        TargetDataLine targetDataLine;
+        try {
+            targetDataLine = (TargetDataLine) AudioSystem.getLine(info);
+            targetDataLine.open(format);
+            targetDataLine.start();
+        } catch (LineUnavailableException e) {
+            System.err.println("Error opening target data line: " + e.getMessage());
+            return;
+        }
+
+        // Main loop to continuously read data and apply Voice Activity Detection
+        while (targetDataLine.isOpen()) {
+            byte[] data = new byte[WINDOW_SIZE_SAMPLES];
+
+            int numBytesRead = targetDataLine.read(data, 0, data.length);
+            if (numBytesRead <= 0) {
+                System.err.println("Error reading data from target data line.");
+                continue;
+            }
+
+            // Apply the Voice Activity Detector to the data and get the result
+            Map<String, Double> detectResult;
+            try {
+                detectResult = vadDetector.apply(data, true);
+            } catch (Exception e) {
+                System.err.println("Error applying VAD detector: " + e.getMessage());
+                continue;
+            }
+
+            if (!detectResult.isEmpty()) {
+                System.out.println(detectResult);
+            }
+        }
+
+        // Close the target data line to release audio resources
+        targetDataLine.close();
+    }
+}
diff --git a/examples/java-example/src/main/java/org/example/SlieroVadDetector.java b/examples/java-example/src/main/java/org/example/SlieroVadDetector.java
new file mode 100644
index 0000000..dd2eecd
--- /dev/null
+++ b/examples/java-example/src/main/java/org/example/SlieroVadDetector.java
@@ -0,0 +1,145 @@
+package org.example;
+
+import ai.onnxruntime.OrtException;
+
+import java.math.BigDecimal;
+import java.math.RoundingMode;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.Map;
+
+
+public class SlieroVadDetector {
+    // OnnxModel model used for speech processing
+    private final SlieroVadOnnxModel model;
+    // Threshold for speech start
+    private final float startThreshold;
+    // Threshold for speech end
+    private final float endThreshold;
+    // Sampling rate
+    private final int samplingRate;
+    // Minimum number of silence samples to determine the end threshold of speech
+    private final float minSilenceSamples;
+    // Additional number of samples for speech start or end to calculate speech start or end time
+    private final float speechPadSamples;
+    // Whether in the triggered state (i.e. whether speech is being detected)
+    private boolean triggered;
+    // Temporarily stored number of speech end samples
+    private int tempEnd;
+    // Number of samples currently being processed
+    private int currentSample;
+
+
+    public SlieroVadDetector(String modelPath,
+                             float startThreshold,
+                             float endThreshold,
+                             int samplingRate,
+                             int minSilenceDurationMs,
+                             int speechPadMs) throws OrtException {
+        // Check if the sampling rate is 8000 or 16000, if not, throw an exception
+        if (samplingRate != 8000 && samplingRate != 16000) {
+            throw new IllegalArgumentException("does not support sampling rates other than [8000, 16000]");
+        }
+
+        // Initialize the parameters
+        this.model = new SlieroVadOnnxModel(modelPath);
+        this.startThreshold = startThreshold;
+        this.endThreshold = endThreshold;
+        this.samplingRate = samplingRate;
+        this.minSilenceSamples = samplingRate * minSilenceDurationMs / 1000f;
+        this.speechPadSamples = samplingRate * speechPadMs / 1000f;
+        // Reset the state
+        reset();
+    }
+
+    // Method to reset the state, including the model state, trigger state, temporary end time, and current sample count
+    public void reset() {
+        model.resetStates();
+        triggered = false;
+        tempEnd = 0;
+        currentSample = 0;
+    }
+
+    // apply method for processing the audio array, returning possible speech start or end times
+    public Map<String, Double> apply(byte[] data, boolean returnSeconds) {
+
+        // Convert the byte array to a float array
+        float[] audioData = new float[data.length / 2];
+        for (int i = 0; i < audioData.length; i++) {
+            audioData[i] = ((data[i * 2] & 0xff) | (data[i * 2 + 1] << 8)) / 32767.0f;
+        }
+
+        // Get the length of the audio array as the window size
+        int windowSizeSamples = audioData.length;
+        // Update the current sample count
+        currentSample += windowSizeSamples;
+
+        // Call the model to get the prediction probability of speech
+        float speechProb = 0;
+        try {
+            speechProb = model.call(new float[][]{audioData}, samplingRate)[0];
+        } catch (OrtException e) {
+            throw new RuntimeException(e);
+        }
+
+        // If the speech probability is greater than the threshold and the temporary end time is not 0, reset the temporary end time
+        // This indicates that the speech duration has exceeded expectations and needs to recalculate the end time
+        if (speechProb >= startThreshold && tempEnd != 0) {
+            tempEnd = 0;
+        }
+
+        // If the speech probability is greater than the threshold and not in the triggered state, set to triggered state and calculate the speech start time
+        if (speechProb >= startThreshold && !triggered) {
+            triggered = true;
+            int speechStart = (int) (currentSample - speechPadSamples);
+            speechStart = Math.max(speechStart, 0);
+            Map<String, Double> result = new HashMap<>();
+            // Decide whether to return the result in seconds or sample count based on the returnSeconds parameter
+            if (returnSeconds) {
+                double speechStartSeconds = speechStart / (double) samplingRate;
+                double roundedSpeechStart = BigDecimal.valueOf(speechStartSeconds).setScale(1, RoundingMode.HALF_UP).doubleValue();
+                result.put("start", roundedSpeechStart);
+            } else {
+                result.put("start", (double) speechStart);
+            }
+
+            return result;
+        }
+
+        // If the speech probability is less than a certain threshold and in the triggered state, calculate the speech end time
+        if (speechProb < endThreshold && triggered) {
+            // Initialize or update the temporary end time
+            if (tempEnd == 0) {
+                tempEnd = currentSample;
+            }
+            // If the number of silence samples between the current sample and the temporary end time is less than the minimum silence samples, return null
+            // This indicates that it is not yet possible to determine whether the speech has ended
+            if (currentSample - tempEnd < minSilenceSamples) {
+                return Collections.emptyMap();
+            } else {
+                // Calculate the speech end time, reset the trigger state and temporary end time
+                int speechEnd = (int) (tempEnd + speechPadSamples);
+                tempEnd = 0;
+                triggered = false;
+                Map<String, Double> result = new HashMap<>();
+
+                if (returnSeconds) {
+                    double speechEndSeconds = speechEnd / (double) samplingRate;
+                    double roundedSpeechEnd = BigDecimal.valueOf(speechEndSeconds).setScale(1, RoundingMode.HALF_UP).doubleValue();
+                    result.put("end", roundedSpeechEnd);
+                } else {
+                    result.put("end", (double) speechEnd);
+                }
+                return result;
+            }
+        }
+
+        // If the above conditions are not met, return null by default
+        return Collections.emptyMap();
+    }
+
+    public void close() throws OrtException {
+        reset();
+        model.close();
+    }
+}
diff --git a/examples/java-example/src/main/java/org/example/SlieroVadOnnxModel.java b/examples/java-example/src/main/java/org/example/SlieroVadOnnxModel.java
new file mode 100644
index 0000000..e9fd8b8
--- /dev/null
+++ b/examples/java-example/src/main/java/org/example/SlieroVadOnnxModel.java
@@ -0,0 +1,180 @@
+package org.example;
+
+import ai.onnxruntime.OnnxTensor;
+import ai.onnxruntime.OrtEnvironment;
+import ai.onnxruntime.OrtException;
+import ai.onnxruntime.OrtSession;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+public class SlieroVadOnnxModel {
+    // Define private variable OrtSession
+    private final OrtSession session;
+    private float[][][] h;
+    private float[][][] c;
+    // Define the last sample rate
+    private int lastSr = 0;
+    // Define the last batch size
+    private int lastBatchSize = 0;
+    // Define a list of supported sample rates
+    private static final List<Integer> SAMPLE_RATES = Arrays.asList(8000, 16000);
+
+    // Constructor
+    public SlieroVadOnnxModel(String modelPath) throws OrtException {
+        // Get the ONNX runtime environment
+        OrtEnvironment env = OrtEnvironment.getEnvironment();
+        // Create an ONNX session options object
+        OrtSession.SessionOptions opts = new OrtSession.SessionOptions();
+        // Set the InterOp thread count to 1, InterOp threads are used for parallel processing of different computation graph operations
+        opts.setInterOpNumThreads(1);
+        // Set the IntraOp thread count to 1, IntraOp threads are used for parallel processing within a single operation
+        opts.setIntraOpNumThreads(1);
+        // Add a CPU device, setting to false disables CPU execution optimization
+        opts.addCPU(true);
+        // Create an ONNX session using the environment, model path, and options
+        session = env.createSession(modelPath, opts);
+        // Reset states
+        resetStates();
+    }
+
+    /**
+     * Reset states
+     */
+    void resetStates() {
+        h = new float[2][1][64];
+        c = new float[2][1][64];
+        lastSr = 0;
+        lastBatchSize = 0;
+    }
+
+    public void close() throws OrtException {
+        session.close();
+    }
+
+    /**
+     * Define inner class ValidationResult
+     */
+    public static class ValidationResult {
+        public final float[][] x;
+        public final int sr;
+
+        // Constructor
+        public ValidationResult(float[][] x, int sr) {
+            this.x = x;
+            this.sr = sr;
+        }
+    }
+
+    /**
+     * Function to validate input data
+     */
+    private ValidationResult validateInput(float[][] x, int sr) {
+        // Process the input data with dimension 1
+        if (x.length == 1) {
+            x = new float[][]{x[0]};
+        }
+        // Throw an exception when the input data dimension is greater than 2
+        if (x.length > 2) {
+            throw new IllegalArgumentException("Incorrect audio data dimension: " + x[0].length);
+        }
+
+        // Process the input data when the sample rate is not equal to 16000 and is a multiple of 16000
+        if (sr != 16000 && (sr % 16000 == 0)) {
+            int step = sr / 16000;
+            float[][] reducedX = new float[x.length][];
+
+            for (int i = 0; i < x.length; i++) {
+                float[] current = x[i];
+                float[] newArr = new float[(current.length + step - 1) / step];
+
+                for (int j = 0, index = 0; j < current.length; j += step, index++) {
+                    newArr[index] = current[j];
+                }
+
+                reducedX[i] = newArr;
+            }
+
+            x = reducedX;
+            sr = 16000;
+        }
+
+        // If the sample rate is not in the list of supported sample rates, throw an exception
+        if (!SAMPLE_RATES.contains(sr)) {
+            throw new IllegalArgumentException("Only supports sample rates " + SAMPLE_RATES + " (or multiples of 16000)");
+        }
+
+        // If the input audio block is too short, throw an exception
+        if (((float) sr) / x[0].length > 31.25) {
+            throw new IllegalArgumentException("Input audio is too short");
+        }
+
+        // Return the validated result
+        return new ValidationResult(x, sr);
+    }
+
+    /**
+     * Method to call the ONNX model
+     */
+    public float[] call(float[][] x, int sr) throws OrtException {
+        ValidationResult result = validateInput(x, sr);
+        x = result.x;
+        sr = result.sr;
+
+        int batchSize = x.length;
+
+        if (lastBatchSize == 0 || lastSr != sr || lastBatchSize != batchSize) {
+            resetStates();
+        }
+
+        OrtEnvironment env = OrtEnvironment.getEnvironment();
+
+        OnnxTensor inputTensor = null;
+        OnnxTensor hTensor = null;
+        OnnxTensor cTensor = null;
+        OnnxTensor srTensor = null;
+        OrtSession.Result ortOutputs = null;
+
+        try {
+            // Create input tensors
+            inputTensor = OnnxTensor.createTensor(env, x);
+            hTensor = OnnxTensor.createTensor(env, h);
+            cTensor = OnnxTensor.createTensor(env, c);
+            srTensor = OnnxTensor.createTensor(env, new long[]{sr});
+
+            Map<String, OnnxTensor> inputs = new HashMap<>();
+            inputs.put("input", inputTensor);
+            inputs.put("sr", srTensor);
+            inputs.put("h", hTensor);
+            inputs.put("c", cTensor);
+
+            // Call the ONNX model for calculation
+            ortOutputs = session.run(inputs);
+            // Get the output results
+            float[][] output = (float[][]) ortOutputs.get(0).getValue();
+            h = (float[][][]) ortOutputs.get(1).getValue();
+            c = (float[][][]) ortOutputs.get(2).getValue();
+
+            lastSr = sr;
+            lastBatchSize = batchSize;
+            return output[0];
+        } finally {
+            if (inputTensor != null) {
+                inputTensor.close();
+            }
+            if (hTensor != null) {
+                hTensor.close();
+            }
+            if (cTensor != null) {
+                cTensor.close();
+            }
+            if (srTensor != null) {
+                srTensor.close();
+            }
+            if (ortOutputs != null) {
+                ortOutputs.close();
+            }
+        }
+    }
+}