Add C# API for FunASR Nano (#3031)

.github/scripts/test-dot-net.sh

@@ -4,7 +4,19 @@ set -ex
 
 cd dotnet-examples/
 
-cd ./version-test
+cd ./vad-non-streaming-funasr-nano
+./run-ten-vad.sh
+rm -fv *.onnx
+
+./run.sh
+rm -fv *.onnx
+
+cd ../non-streaming-funasr-nano-decode-files
+./run.sh
+ls -lh
+rm -rf sherpa-onnx-funasr-*
+
+cd ../version-test
 ./run.sh
 ls -lh
 

dotnet-examples/non-streaming-funasr-nano-decode-files/Program.cs

@@ -0,0 +1,35 @@
+// Copyright (c)  2026  Xiaomi Corporation
+//
+// This file shows how to use a FunASR Nano model for speech recognition.
+//
+// You can find the model doc at
+// https://k2-fsa.github.io/sherpa/onnx/funasr-nano.html
+using SherpaOnnx;
+
+class NonStreamingFunAsrNano
+{
+  static void Main(string[] args)
+  {
+    // please download model files from
+    // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+    var config = new OfflineRecognizerConfig();
+    config.ModelConfig.FunAsrNano.EncoderAdaptor = "./sherpa-onnx-funasr-nano-int8-2025-12-30/encoder_adaptor.int8.onnx";
+    config.ModelConfig.FunAsrNano.LLM = "./sherpa-onnx-funasr-nano-int8-2025-12-30/llm.int8.onnx";
+    config.ModelConfig.FunAsrNano.Embedding = "./sherpa-onnx-funasr-nano-int8-2025-12-30/embedding.int8.onnx";
+    config.ModelConfig.FunAsrNano.Tokenizer = "./sherpa-onnx-funasr-nano-int8-2025-12-30/Qwen3-0.6B";
+    config.ModelConfig.Tokens = "";
+    config.ModelConfig.Debug = 1;
+    var recognizer = new OfflineRecognizer(config);
+
+    var testWaveFilename = "./sherpa-onnx-funasr-nano-int8-2025-12-30/test_wavs/lyrics.wav";
+    var reader = new WaveReader(testWaveFilename);
+    var stream = recognizer.CreateStream();
+    stream.AcceptWaveform(reader.SampleRate, reader.Samples);
+    recognizer.Decode(stream);
+    var text = stream.Result.Text;
+    Console.WriteLine("Text: {0}", text);
+  }
+}
+
+
+

dotnet-examples/non-streaming-funasr-nano-decode-files/non-streaming-funasr-nano-decode-files.csproj

@@ -0,0 +1,15 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <RootNamespace>non_streaming_funasr_nano_decode_files</RootNamespace>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\Common\Common.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet-examples/non-streaming-funasr-nano-decode-files/run.sh

@@ -0,0 +1,11 @@
+#!/usr/bin/env bash
+
+set -ex
+
+if [ ! -f ./sherpa-onnx-funasr-nano-int8-2025-12-30/embedding.int8.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2 
+  tar xvf sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+  rm sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+fi
+
+dotnet run

dotnet-examples/sherpa-onnx.sln

@@ -47,6 +47,10 @@ Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "kitten-tts-play", "kitten-t
 EndProject
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "offline-audio-tagging", "offline-audio-tagging\offline-audio-tagging.csproj", "{0EBE2CE5-8940-4472-8A38-6A0E976E678F}"
 EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "non-streaming-funasr-nano-decode-files", "non-streaming-funasr-nano-decode-files\non-streaming-funasr-nano-decode-files.csproj", "{32F7534B-117E-4D1D-BAED-A1D1A6C6A62C}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "vad-non-streaming-funasr-nano", "vad-non-streaming-funasr-nano\vad-non-streaming-funasr-nano.csproj", "{32C8C12B-D7DB-455E-B35C-945A745520CC}"
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -141,6 +145,14 @@ Global
 		{0EBE2CE5-8940-4472-8A38-6A0E976E678F}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{0EBE2CE5-8940-4472-8A38-6A0E976E678F}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{0EBE2CE5-8940-4472-8A38-6A0E976E678F}.Release|Any CPU.Build.0 = Release|Any CPU
+		{32F7534B-117E-4D1D-BAED-A1D1A6C6A62C}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{32F7534B-117E-4D1D-BAED-A1D1A6C6A62C}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{32F7534B-117E-4D1D-BAED-A1D1A6C6A62C}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{32F7534B-117E-4D1D-BAED-A1D1A6C6A62C}.Release|Any CPU.Build.0 = Release|Any CPU
+		{32C8C12B-D7DB-455E-B35C-945A745520CC}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{32C8C12B-D7DB-455E-B35C-945A745520CC}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{32C8C12B-D7DB-455E-B35C-945A745520CC}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{32C8C12B-D7DB-455E-B35C-945A745520CC}.Release|Any CPU.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

dotnet-examples/vad-non-streaming-funasr-nano/Program.cs

@@ -0,0 +1,122 @@
+// Copyright (c)  2026  Xiaomi Corporation
+//
+// This file shows how to use a silero_vad model or ten-vad model
+// with a non-streaming FunASR Nano for speech recognition.
+using SherpaOnnx;
+using System.IO;
+
+
+class VadNonStreamingFunAsrNano
+{
+  static void Main(string[] args)
+  {
+    // please download model files from
+    // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+    var config = new OfflineRecognizerConfig();
+    config.ModelConfig.FunAsrNano.EncoderAdaptor = "./sherpa-onnx-funasr-nano-int8-2025-12-30/encoder_adaptor.int8.onnx";
+    config.ModelConfig.FunAsrNano.LLM = "./sherpa-onnx-funasr-nano-int8-2025-12-30/llm.int8.onnx";
+    config.ModelConfig.FunAsrNano.Embedding = "./sherpa-onnx-funasr-nano-int8-2025-12-30/embedding.int8.onnx";
+    config.ModelConfig.FunAsrNano.Tokenizer = "./sherpa-onnx-funasr-nano-int8-2025-12-30/Qwen3-0.6B";
+    config.ModelConfig.Tokens = "";
+    config.ModelConfig.Debug = 0;
+    var recognizer = new OfflineRecognizer(config);
+
+    var vadModelConfig = new VadModelConfig();
+    if (File.Exists("./silero_vad.onnx"))
+    {
+      Console.WriteLine("Use silero-vad");
+      vadModelConfig.SileroVad.Model = "./silero_vad.onnx";
+      vadModelConfig.SileroVad.Threshold = 0.3F;
+      vadModelConfig.SileroVad.MinSilenceDuration = 0.5F;
+      vadModelConfig.SileroVad.MinSpeechDuration = 0.25F;
+      vadModelConfig.SileroVad.MaxSpeechDuration = 5.0F;
+      vadModelConfig.SileroVad.WindowSize = 512;
+    }
+    else if (File.Exists("./ten-vad.onnx"))
+    {
+      Console.WriteLine("Use ten-vad");
+      vadModelConfig.TenVad.Model = "./ten-vad.onnx";
+      vadModelConfig.TenVad.Threshold = 0.3F;
+      vadModelConfig.TenVad.MinSilenceDuration = 0.5F;
+      vadModelConfig.TenVad.MinSpeechDuration = 0.25F;
+      vadModelConfig.TenVad.MaxSpeechDuration = 5.0F;
+      vadModelConfig.TenVad.WindowSize = 256;
+    }
+    else
+    {
+      Console.WriteLine("Please download ./silero_vad.onnx or ./ten-vad.onnx");
+      return;
+    }
+    vadModelConfig.Debug = 0;
+
+    var vad = new VoiceActivityDetector(vadModelConfig, 60);
+
+    var testWaveFilename = "./lei-jun-test.wav";
+    var reader = new WaveReader(testWaveFilename);
+
+    int numSamples = reader.Samples.Length;
+    int windowSize = vadModelConfig.SileroVad.WindowSize;
+
+    if (vadModelConfig.TenVad.Model != "")
+    {
+      windowSize = vadModelConfig.TenVad.WindowSize;
+    }
+
+    int sampleRate = vadModelConfig.SampleRate;
+    int numIter = numSamples / windowSize;
+
+    for (int i = 0; i != numIter; ++i)
+    {
+      int start = i * windowSize;
+      var samples = new float[windowSize];
+      Array.Copy(reader.Samples, start, samples, 0, windowSize);
+      vad.AcceptWaveform(samples);
+      if (vad.IsSpeechDetected())
+      {
+        while (!vad.IsEmpty())
+        {
+          SpeechSegment segment = vad.Front();
+          var startTime = segment.Start / (float)sampleRate;
+          var duration = segment.Samples.Length / (float)sampleRate;
+
+          OfflineStream stream = recognizer.CreateStream();
+          stream.AcceptWaveform(sampleRate, segment.Samples);
+          recognizer.Decode(stream);
+          var text = stream.Result.Text;
+
+          if (!string.IsNullOrEmpty(text))
+          {
+            Console.WriteLine("{0}--{1}: {2}", string.Format("{0:0.00}", startTime),
+                string.Format("{0:0.00}", startTime + duration), text);
+          }
+
+          vad.Pop();
+        }
+      }
+    }
+
+    vad.Flush();
+
+    while (!vad.IsEmpty())
+    {
+      var segment = vad.Front();
+      float startTime = segment.Start / (float)sampleRate;
+      float duration = segment.Samples.Length / (float)sampleRate;
+
+      var stream = recognizer.CreateStream();
+      stream.AcceptWaveform(sampleRate, segment.Samples);
+      recognizer.Decode(stream);
+      var text = stream.Result.Text;
+
+      if (!string.IsNullOrEmpty(text))
+      {
+        Console.WriteLine("{0}--{1}: {2}", string.Format("{0:0.00}", startTime),
+            string.Format("{0:0.00}", startTime + duration), text);
+      }
+
+      vad.Pop();
+    }
+  }
+}
+
+

dotnet-examples/vad-non-streaming-funasr-nano/run-ten-vad.sh

@@ -0,0 +1,19 @@
+#!/usr/bin/env bash
+
+set -ex
+
+if [ ! -f ./ten-vad.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/ten-vad.onnx
+fi
+
+if [ ! -f ./lei-jun-test.wav ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
+fi
+
+if [ ! -f ./sherpa-onnx-funasr-nano-int8-2025-12-30/embedding.int8.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+  tar xvf sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+  rm sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+fi
+
+dotnet run

dotnet-examples/vad-non-streaming-funasr-nano/run.sh

@@ -0,0 +1,19 @@
+#!/usr/bin/env bash
+
+set -ex
+
+if [ ! -f ./silero_vad.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
+fi
+
+if [ ! -f ./lei-jun-test.wav ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
+fi
+
+if [ ! -f ./sherpa-onnx-funasr-nano-int8-2025-12-30/embedding.int8.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+  tar xvf sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+  rm sherpa-onnx-funasr-nano-int8-2025-12-30.tar.bz2
+fi
+
+dotnet run

dotnet-examples/vad-non-streaming-funasr-nano/vad-non-streaming-funasr-nano.csproj

@@ -0,0 +1,15 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <RootNamespace>vad_non_streaming_funasr_nano</RootNamespace>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\Common\Common.csproj" />
+  </ItemGroup>
+
+</Project>

scripts/dotnet/OfflineFunAsrNanoModel.cs

@@ -0,0 +1,48 @@
+/// Copyright (c)  2025  Xiaomi Corporation (authors: Fangjun Kuang)
+
+using System.Runtime.InteropServices;
+
+namespace SherpaOnnx
+{
+
+    [StructLayout(LayoutKind.Sequential)]
+    public struct OfflineFunAsrNanoModelConfig
+    {
+        public OfflineFunAsrNanoModelConfig()
+        {
+            EncoderAdaptor = "";
+            LLM = "";
+            Embedding = "";
+            Tokenizer = "";
+            SystemPrompt = "You are a helpful assistant.";
+            UserPrompt = "语音转写：";
+            MaxNewTokens = 512;
+            Temperature = 1e-6F;
+            TopP = 0.8F;
+            Seed = 42;
+        }
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string EncoderAdaptor;
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string LLM;
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string Embedding;
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string Tokenizer;
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string SystemPrompt;
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string UserPrompt;
+
+        public int MaxNewTokens;
+        public float Temperature;
+        public float TopP;
+        public int Seed;
+    }
+}

scripts/dotnet/OfflineModelConfig.cs

@@ -32,6 +32,7 @@ namespace SherpaOnnx
             WenetCtc = new OfflineWenetCtcModelConfig();
             Omnilingual = new OfflineOmnilingualAsrCtcModelConfig();
             MedAsr = new OfflineMedAsrCtcModelConfig();
+            FunAsrNano = new OfflineFunAsrNanoModelConfig();
         }
         public OfflineTransducerModelConfig Transducer;
         public OfflineParaformerModelConfig Paraformer;
@@ -70,5 +71,6 @@ namespace SherpaOnnx
         public OfflineWenetCtcModelConfig WenetCtc;
         public OfflineOmnilingualAsrCtcModelConfig Omnilingual;
         public OfflineMedAsrCtcModelConfig MedAsr;
+        public OfflineFunAsrNanoModelConfig FunAsrNano;
     }
 }

scripts/dotnet/generate.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 # Copyright (c)  2023  Xiaomi Corporation
 
-import argparse
+import glob
 import os
 import re
 from pathlib import Path
@@ -28,7 +28,6 @@ def read_proj_file(filename):
 
 
 def get_dict():
-    version = get_version()
     return {
         "version": get_version(),
     }
@@ -55,17 +54,18 @@ def process_linux(s, rid):
 
 
 def process_macos(s, rid):
-    libs = [
-        "libonnxruntime.1.17.1.dylib",
-        "libsherpa-onnx-c-api.dylib",
-    ]
-    prefix = f"{src_dir}/macos-{rid}/"
-    libs = [prefix + lib for lib in libs]
-    libs = "\n      ;".join(libs)
+    lib_dir = os.path.join(src_dir, f"macos-{rid}")
+    onnx_libs = glob.glob(os.path.join(lib_dir, "libonnxruntime*.dylib"))
+    if not onnx_libs:
+        raise FileNotFoundError(f"No libonnxruntime*.dylib found in {lib_dir}")
+
+    other_libs = [os.path.join(lib_dir, "libsherpa-onnx-c-api.dylib")]
+    libs = onnx_libs + other_libs
+    libs_str = "\n      ;".join(libs)
 
     d = get_dict()
     d["dotnet_rid"] = f"osx-{rid}"
-    d["libs"] = libs
+    d["libs"] = libs_str
 
     environment = jinja2.Environment()
     template = environment.from_string(s)
@@ -80,8 +80,6 @@ def process_windows(s, rid):
         "sherpa-onnx-c-api.dll",
     ]
 
-    version = get_version()
-
     prefix = f"{src_dir}/windows-{rid}/"
     libs = [prefix + lib for lib in libs]
     libs = "\n      ;".join(libs)

scripts/go/release.sh

@@ -94,7 +94,7 @@ function osx() {
   cp -v sherpa_onnx/lib/*.dylib $dst/
 
   pushd $dst
-  cp -v libonnxruntime.1.17.1.dylib libonnxruntime.dylib
+  cp -v libonnxruntime.*.dylib libonnxruntime.dylib
   popd
 
   cd ..
@@ -112,7 +112,7 @@ function osx() {
   cp -v sherpa_onnx/lib/*.dylib $dst/
 
   pushd $dst
-  cp -v libonnxruntime.1.17.1.dylib libonnxruntime.dylib
+  cp -v libonnxruntime.*.dylib libonnxruntime.dylib
   popd
 
   cd ..