修复CalculateProb方法计算句子EndOffset的bug

修改语法提示

examples/csharp/Program.cs

@@ -21,7 +21,7 @@ class Program
                 MIN_SPEECH_DURATION_MS, MAX_SPEECH_DURATION_SECONDS, MIN_SILENCE_DURATION_MS, SPEECH_PAD_MS);
             List<SileroSpeechSegment> speechTimeList = vadDetector.GetSpeechSegmentList(new FileInfo(EXAMPLE_WAV_FILE));
             //Console.WriteLine(speechTimeList.ToJson());
-            StringBuilder sb = new StringBuilder();
+            StringBuilder sb = new();
             foreach (var speechSegment in speechTimeList)
             {
                 sb.Append($"start second: {speechSegment.StartSecond}, end second: {speechSegment.EndSecond}\n");

examples/csharp/SileroVadDetector.cs

@@ -53,28 +53,26 @@ public class SileroVadDetector
     {
         Reset();
 
-        using (var audioFile = new AudioFileReader(wavFile.FullName))
+        using var audioFile = new AudioFileReader(wavFile.FullName);
+        List<float> speechProbList = [];
+        this._audioLengthSamples = (int)(audioFile.Length / 2);
+        float[] buffer = new float[this._windowSizeSample];
+
+        while (audioFile.Read(buffer, 0, buffer.Length) > 0)
         {
-            List<float> speechProbList = new List<float>();
-            this._audioLengthSamples = (int)(audioFile.Length / 2);
-            float[] buffer = new float[this._windowSizeSample];
-
-            while (audioFile.Read(buffer, 0, buffer.Length) > 0)
-            {
-                float speechProb = _model.Call(new[] { buffer }, _samplingRate)[0];
-                speechProbList.Add(speechProb);
-            }
-
-            return CalculateProb(speechProbList);
+            float speechProb = _model.Call([buffer], _samplingRate)[0];
+            speechProbList.Add(speechProb);
         }
+
+        return CalculateProb(speechProbList);
     }
 
     private List<SileroSpeechSegment> CalculateProb(List<float> speechProbList)
     {
-        List<SileroSpeechSegment> result = new List<SileroSpeechSegment>();
+        List<SileroSpeechSegment> result = [];
         bool triggered = false;
         int tempEnd = 0, prevEnd = 0, nextStart = 0;
-        SileroSpeechSegment segment = new SileroSpeechSegment();
+        SileroSpeechSegment segment = new();
 
         for (int i = 0; i < speechProbList.Count; i++)
         {
@@ -164,7 +162,8 @@ public class SileroVadDetector
 
         if (segment.StartOffset != null && (_audioLengthSamples - segment.StartOffset) > _minSpeechSamples)
         {
-            segment.EndOffset = _audioLengthSamples;
+            //segment.EndOffset = _audioLengthSamples;
+            segment.EndOffset = speechProbList.Count * _windowSizeSample;
             result.Add(segment);
         }
 
@@ -182,7 +181,7 @@ public class SileroVadDetector
                 int silenceDuration = nextItem.StartOffset.Value - item.EndOffset.Value;
                 if (silenceDuration < 2 * _speechPadSamples)
                 {
-                    item.EndOffset = item.EndOffset + (silenceDuration / 2);
+                    item.EndOffset += (silenceDuration / 2);
                     nextItem.StartOffset = Math.Max(0, nextItem.StartOffset.Value - (silenceDuration / 2));
                 }
                 else
@@ -200,9 +199,9 @@ public class SileroVadDetector
         return MergeListAndCalculateSecond(result, _samplingRate);
     }
 
-    private List<SileroSpeechSegment> MergeListAndCalculateSecond(List<SileroSpeechSegment> original, int samplingRate)
+    private static List<SileroSpeechSegment> MergeListAndCalculateSecond(List<SileroSpeechSegment> original, int samplingRate)
     {
-        List<SileroSpeechSegment> result = new List<SileroSpeechSegment>();
+        List<SileroSpeechSegment> result = [];
         if (original == null || original.Count == 0)
         {
             return result;
@@ -216,7 +215,10 @@ public class SileroVadDetector
             for (int i = 1; i < original.Count; i++)
             {
                 SileroSpeechSegment segment = original[i];
+                if (i == 235)
+                {
 
+                }
                 if (segment.StartOffset > right)
                 {
                     result.Add(new SileroSpeechSegment(left, right,
@@ -242,7 +244,7 @@ public class SileroVadDetector
         return result;
     }
 
-    private float CalculateSecondByOffset(int offset, int samplingRate)
+    private static float CalculateSecondByOffset(int offset, int samplingRate)
     {
         float secondValue = offset * 1.0f / samplingRate;
         return (float)Math.Floor(secondValue * 1000.0f) / 1000.0f;

examples/csharp/SileroVadOnnxModel.cs

@@ -1,5 +1,6 @@
 using Microsoft.ML.OnnxRuntime;
 using Microsoft.ML.OnnxRuntime.Tensors;
+
 using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -7,214 +8,208 @@ using System.Linq;
 namespace VADdotnet;
 
 
-    public class SileroVadOnnxModel : IDisposable
+public class SileroVadOnnxModel : IDisposable
+{
+    private readonly InferenceSession session;
+    private float[][][] state;
+    private float[][] context;
+    private int lastSr = 0;
+    private int lastBatchSize = 0;
+    private static readonly List<int> SAMPLE_RATES = [8000, 16000];
+
+    public SileroVadOnnxModel(string modelPath)
     {
-        private readonly InferenceSession session;
-        private float[][][] state;
-        private float[][] context;
-        private int lastSr = 0;
-        private int lastBatchSize = 0;
-        private static readonly List<int> SAMPLE_RATES = new List<int> { 8000, 16000 };
-
-        public SileroVadOnnxModel(string modelPath)
+        var sessionOptions = new SessionOptions
         {
-            var sessionOptions = new SessionOptions();
-            sessionOptions.InterOpNumThreads = 1;
-            sessionOptions.IntraOpNumThreads = 1;
-            sessionOptions.EnableCpuMemArena = true;
+            InterOpNumThreads = 1,
+            IntraOpNumThreads = 1,
+            EnableCpuMemArena = true
+        };
 
-            session = new InferenceSession(modelPath, sessionOptions);
+        session = new InferenceSession(modelPath, sessionOptions);
+        ResetStates();
+    }
+
+    public void ResetStates()
+    {
+        state = new float[2][][];
+        state[0] = new float[1][];
+        state[1] = new float[1][];
+        state[0][0] = new float[128];
+        state[1][0] = new float[128];
+        context = [];
+        lastSr = 0;
+        lastBatchSize = 0;
+    }
+
+    public void Dispose()
+    {
+        GC.SuppressFinalize(this);
+    }
+
+    public class ValidationResult(float[][] x, int sr)
+    {
+        public float[][] X { get; } = x;
+        public int Sr { get; } = sr;
+    }
+
+    private static ValidationResult ValidateInput(float[][] x, int sr)
+    {
+        if (x.Length == 1)
+        {
+            x = [x[0]];
+        }
+        if (x.Length > 2)
+        {
+            throw new ArgumentException($"Incorrect audio data dimension: {x[0].Length}");
+        }
+
+        if (sr != 16000 && (sr % 16000 == 0))
+        {
+            int step = sr / 16000;
+            float[][] reducedX = new float[x.Length][];
+
+            for (int i = 0; i < x.Length; i++)
+            {
+                float[] current = x[i];
+                float[] newArr = new float[(current.Length + step - 1) / step];
+
+                for (int j = 0, index = 0; j < current.Length; j += step, index++)
+                {
+                    newArr[index] = current[j];
+                }
+
+                reducedX[i] = newArr;
+            }
+
+            x = reducedX;
+            sr = 16000;
+        }
+
+        if (!SAMPLE_RATES.Contains(sr))
+        {
+            throw new ArgumentException($"Only supports sample rates {string.Join(", ", SAMPLE_RATES)} (or multiples of 16000)");
+        }
+
+        if (((float)sr) / x[0].Length > 31.25)
+        {
+            throw new ArgumentException("Input audio is too short");
+        }
+
+        return new ValidationResult(x, sr);
+    }
+
+    private static float[][] Concatenate(float[][] a, float[][] b)
+    {
+        if (a.Length != b.Length)
+        {
+            throw new ArgumentException("The number of rows in both arrays must be the same.");
+        }
+
+        int rows = a.Length;
+        int colsA = a[0].Length;
+        int colsB = b[0].Length;
+        float[][] result = new float[rows][];
+
+        for (int i = 0; i < rows; i++)
+        {
+            result[i] = new float[colsA + colsB];
+            Array.Copy(a[i], 0, result[i], 0, colsA);
+            Array.Copy(b[i], 0, result[i], colsA, colsB);
+        }
+
+        return result;
+    }
+
+    private static float[][] GetLastColumns(float[][] array, int contextSize)
+    {
+        int rows = array.Length;
+        int cols = array[0].Length;
+
+        if (contextSize > cols)
+        {
+            throw new ArgumentException("contextSize cannot be greater than the number of columns in the array.");
+        }
+
+        float[][] result = new float[rows][];
+
+        for (int i = 0; i < rows; i++)
+        {
+            result[i] = new float[contextSize];
+            Array.Copy(array[i], cols - contextSize, result[i], 0, contextSize);
+        }
+
+        return result;
+    }
+
+    public float[] Call(float[][] x, int sr)
+    {
+        var result = ValidateInput(x, sr);
+        x = result.X;
+        sr = result.Sr;
+        int numberSamples = sr == 16000 ? 512 : 256;
+
+        if (x[0].Length != numberSamples)
+        {
+            throw new ArgumentException($"Provided number of samples is {x[0].Length} (Supported values: 256 for 8000 sample rate, 512 for 16000)");
+        }
+
+        int batchSize = x.Length;
+        int contextSize = sr == 16000 ? 64 : 32;
+
+        if (lastBatchSize == 0)
+        {
+            ResetStates();
+        }
+        if (lastSr != 0 && lastSr != sr)
+        {
+            ResetStates();
+        }
+        if (lastBatchSize != 0 && lastBatchSize != batchSize)
+        {
             ResetStates();
         }
 
-        public void ResetStates()
+        if (context.Length == 0)
         {
-            state = new float[2][][];
-            state[0] = new float[1][];
-            state[1] = new float[1][];
-            state[0][0] = new float[128];
-            state[1][0] = new float[128];
-            context = Array.Empty<float[]>();
-            lastSr = 0;
-            lastBatchSize = 0;
-        }
-
-        public void Dispose()
-        {
-            session?.Dispose();
-        }
-
-        public class ValidationResult
-        {
-            public float[][] X { get; }
-            public int Sr { get; }
-
-            public ValidationResult(float[][] x, int sr)
+            context = new float[batchSize][];
+            for (int i = 0; i < batchSize; i++)
             {
-                X = x;
-                Sr = sr;
+                context[i] = new float[contextSize];
             }
         }
 
-        private ValidationResult ValidateInput(float[][] x, int sr)
-        {
-            if (x.Length == 1)
+        x = Concatenate(context, x);
+
+        var inputs = new List<NamedOnnxValue>
             {
-                x = new float[][] { x[0] };
-            }
-            if (x.Length > 2)
-            {
-                throw new ArgumentException($"Incorrect audio data dimension: {x[0].Length}");
-            }
-
-            if (sr != 16000 && (sr % 16000 == 0))
-            {
-                int step = sr / 16000;
-                float[][] reducedX = new float[x.Length][];
-
-                for (int i = 0; i < x.Length; i++)
-                {
-                    float[] current = x[i];
-                    float[] newArr = new float[(current.Length + step - 1) / step];
-
-                    for (int j = 0, index = 0; j < current.Length; j += step, index++)
-                    {
-                        newArr[index] = current[j];
-                    }
-
-                    reducedX[i] = newArr;
-                }
-
-                x = reducedX;
-                sr = 16000;
-            }
-
-            if (!SAMPLE_RATES.Contains(sr))
-            {
-                throw new ArgumentException($"Only supports sample rates {string.Join(", ", SAMPLE_RATES)} (or multiples of 16000)");
-            }
-
-            if (((float)sr) / x[0].Length > 31.25)
-            {
-                throw new ArgumentException("Input audio is too short");
-            }
-
-            return new ValidationResult(x, sr);
-        }
-
-        private static float[][] Concatenate(float[][] a, float[][] b)
-        {
-            if (a.Length != b.Length)
-            {
-                throw new ArgumentException("The number of rows in both arrays must be the same.");
-            }
-
-            int rows = a.Length;
-            int colsA = a[0].Length;
-            int colsB = b[0].Length;
-            float[][] result = new float[rows][];
-
-            for (int i = 0; i < rows; i++)
-            {
-                result[i] = new float[colsA + colsB];
-                Array.Copy(a[i], 0, result[i], 0, colsA);
-                Array.Copy(b[i], 0, result[i], colsA, colsB);
-            }
-
-            return result;
-        }
-
-        private static float[][] GetLastColumns(float[][] array, int contextSize)
-        {
-            int rows = array.Length;
-            int cols = array[0].Length;
-
-            if (contextSize > cols)
-            {
-                throw new ArgumentException("contextSize cannot be greater than the number of columns in the array.");
-            }
-
-            float[][] result = new float[rows][];
-
-            for (int i = 0; i < rows; i++)
-            {
-                result[i] = new float[contextSize];
-                Array.Copy(array[i], cols - contextSize, result[i], 0, contextSize);
-            }
-
-            return result;
-        }
-
-        public float[] Call(float[][] x, int sr)
-        {
-            var result = ValidateInput(x, sr);
-            x = result.X;
-            sr = result.Sr;
-            int numberSamples = sr == 16000 ? 512 : 256;
-
-            if (x[0].Length != numberSamples)
-            {
-                throw new ArgumentException($"Provided number of samples is {x[0].Length} (Supported values: 256 for 8000 sample rate, 512 for 16000)");
-            }
-
-            int batchSize = x.Length;
-            int contextSize = sr == 16000 ? 64 : 32;
-
-            if (lastBatchSize == 0)
-            {
-                ResetStates();
-            }
-            if (lastSr != 0 && lastSr != sr)
-            {
-                ResetStates();
-            }
-            if (lastBatchSize != 0 && lastBatchSize != batchSize)
-            {
-                ResetStates();
-            }
-
-            if (context.Length == 0)
-            {
-                context = new float[batchSize][];
-                for (int i = 0; i < batchSize; i++)
-                {
-                    context[i] = new float[contextSize];
-                }
-            }
-
-            x = Concatenate(context, x);
-
-            var inputs = new List<NamedOnnxValue>
-            {
-                NamedOnnxValue.CreateFromTensor("input", new DenseTensor<float>(x.SelectMany(a => a).ToArray(), new[] { x.Length, x[0].Length })),
-                NamedOnnxValue.CreateFromTensor("sr", new DenseTensor<long>(new[] { (long)sr }, new[] { 1 })),
-                NamedOnnxValue.CreateFromTensor("state", new DenseTensor<float>(state.SelectMany(a => a.SelectMany(b => b)).ToArray(), new[] { state.Length, state[0].Length, state[0][0].Length }))
+                NamedOnnxValue.CreateFromTensor("input", new DenseTensor<float>(x.SelectMany(a => a).ToArray(), [x.Length, x[0].Length])),
+                NamedOnnxValue.CreateFromTensor("sr", new DenseTensor<long>(new[] { (long)sr }, [1])),
+                NamedOnnxValue.CreateFromTensor("state", new DenseTensor<float>(state.SelectMany(a => a.SelectMany(b => b)).ToArray(), [state.Length, state[0].Length, state[0][0].Length]))
             };
 
-            using (var outputs = session.Run(inputs))
+        using var outputs = session.Run(inputs);
+        var output = outputs.First(o => o.Name == "output").AsTensor<float>();
+        var newState = outputs.First(o => o.Name == "stateN").AsTensor<float>();
+
+        context = GetLastColumns(x, contextSize);
+        lastSr = sr;
+        lastBatchSize = batchSize;
+
+        state = new float[newState.Dimensions[0]][][];
+        for (int i = 0; i < newState.Dimensions[0]; i++)
+        {
+            state[i] = new float[newState.Dimensions[1]][];
+            for (int j = 0; j < newState.Dimensions[1]; j++)
             {
-                var output = outputs.First(o => o.Name == "output").AsTensor<float>();
-                var newState = outputs.First(o => o.Name == "stateN").AsTensor<float>();
-
-                context = GetLastColumns(x, contextSize);
-                lastSr = sr;
-                lastBatchSize = batchSize;
-
-                state = new float[newState.Dimensions[0]][][];
-                for (int i = 0; i < newState.Dimensions[0]; i++)
+                state[i][j] = new float[newState.Dimensions[2]];
+                for (int k = 0; k < newState.Dimensions[2]; k++)
                 {
-                    state[i] = new float[newState.Dimensions[1]][];
-                    for (int j = 0; j < newState.Dimensions[1]; j++)
-                    {
-                        state[i][j] = new float[newState.Dimensions[2]];
-                        for (int k = 0; k < newState.Dimensions[2]; k++)
-                        {
-                            state[i][j][k] = newState[i, j, k];
-                        }
-                    }
+                    state[i][j][k] = newState[i, j, k];
                 }
-
-                return output.ToArray();
             }
         }
+
+        return [.. output];
     }
+}

examples/csharp/VadDotNet.sln

@@ -0,0 +1,25 @@
+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 17
+VisualStudioVersion = 17.14.36616.10 d17.14
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "VadDotNet", "VadDotNet.csproj", "{F36E1741-EDDB-90C7-7501-4911058F8996}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		Release|Any CPU = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{F36E1741-EDDB-90C7-7501-4911058F8996}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{F36E1741-EDDB-90C7-7501-4911058F8996}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{F36E1741-EDDB-90C7-7501-4911058F8996}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{F36E1741-EDDB-90C7-7501-4911058F8996}.Release|Any CPU.Build.0 = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(ExtensibilityGlobals) = postSolution
+		SolutionGuid = {DFC4CEE8-1034-46B4-A5F4-D1649B3543E6}
+	EndGlobalSection
+EndGlobal