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Refactor C# code and support building nuget packages for cross-platforms (#144)

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This commit is contained in:
Fangjun Kuang
2023-05-10 14:53:04 +08:00
committed by GitHub
parent 0bc571f6ee
commit 7969cf44ac
40 changed files with 2050 additions and 2311 deletions
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dotnet-examples/.editorconfig Normal file
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# top-most EditorConfig file
root = true
# Don't use tabs for indentation.
[*]
indent_style = space
# Code files
[*.{cs,csx,vb,vbx}]
indent_size = 2
insert_final_newline = true
charset = utf-8-bom
end_of_line = crlf

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dotnet-examples/.gitignore vendored Normal file
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bin
obj

179
dotnet-examples/offline-decode-files/Program.cs Normal file
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// Copyright (c) 2023 Xiaomi Corporation
// Copyright (c) 2023 by manyeyes
//
// This file shows how to use a non-streaming model to decode files
// Please refer to
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
// to download non-streaming models
using CommandLine.Text;
using CommandLine;
using SherpaOnnx;
using System.Collections.Generic;
using System;
class OfflineDecodeFiles
{
class Options
{
[Option(Required = false, HelpText = "Path to tokens.txt")]
public string Tokens { get; set; }
[Option(Required = false, HelpText = "Path to encoder.onnx. Used only for transducer models")]
public string Encoder { get; set; }
[Option(Required = false, HelpText = "Path to decoder.onnx. Used only for transducer models")]
public string Decoder { get; set; }
[Option(Required = false, HelpText = "Path to joiner.onnx. Used only for transducer models")]
public string Joiner { get; set; }
[Option(Required = false, HelpText = "Path to model.onnx. Used only for paraformer models")]
public string Paraformer { get; set; }
[Option("nemo-ctc", Required = false, HelpText = "Path to model.onnx. Used only for NeMo CTC models")]
public string NeMoCtc { get; set; }
[Option("num-threads", Required = false, Default = 1, HelpText = "Number of threads for computation")]
public int NumThreads { get; set; }
[Option("decoding-method", Required = false, Default = "greedy_search",
HelpText = "Valid decoding methods are: greedy_search, modified_beam_search")]
public string DecodingMethod { get; set; }
[Option("max-active-paths", Required = false, Default = 4,
HelpText = @"Used only when --decoding--method is modified_beam_search.
It specifies number of active paths to keep during the search")]
public int MaxActivePaths { get; set; }
[Option("files", Required = true, HelpText = "Audio files for decoding")]
public IEnumerable<string> Files { get; set; }
}
static void Main(string[] args)
{
var parser = new CommandLine.Parser(with => with.HelpWriter = null);
var parserResult = parser.ParseArguments<Options>(args);
parserResult
.WithParsed<Options>(options => Run(options))
.WithNotParsed(errs => DisplayHelp(parserResult, errs));
}
private static void DisplayHelp<T>(ParserResult<T> result, IEnumerable<Error> errs)
{
string usage = @"
# Zipformer
dotnet run \
--tokens=./sherpa-onnx-zipformer-en-2023-04-01/tokens.txt \
--encoder=./sherpa-onnx-zipformer-en-2023-04-01/encoder-epoch-99-avg-1.onnx \
--decoder=./sherpa-onnx-zipformer-en-2023-04-01/decoder-epoch-99-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-en-2023-04-01/joiner-epoch-99-avg-1.onnx \
--files ./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/0.wav \
./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/1.wav \
./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/8k.wav
Please refer to
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/index.html
to download pre-trained non-streaming zipformer models.
# Paraformer
dotnet run \
--tokens=./sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt \
--paraformer=./sherpa-onnx-paraformer-zh-2023-03-28/model.onnx \
--files ./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/0.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/0.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/1.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/2.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/8k.wav
Please refer to
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-paraformer/index.html
to download pre-trained paraformer models
# NeMo CTC
dotnet run \
--tokens=./sherpa-onnx-nemo-ctc-en-conformer-medium/tokens.txt \
--nemo-ctc=./sherpa-onnx-nemo-ctc-en-conformer-medium/model.onnx \
--num-threads=1 \
--files ./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/0.wav \
./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/1.wav \
./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/8k.wav
Please refer to
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/index.html
to download pre-trained paraformer models
";
var helpText = HelpText.AutoBuild(result, h =>
{
h.AdditionalNewLineAfterOption = false;
h.Heading = usage;
h.Copyright = "Copyright (c) 2023 Xiaomi Corporation";
return HelpText.DefaultParsingErrorsHandler(result, h);
}, e => e);
Console.WriteLine(helpText);
}
private static void Run(Options options)
{
OfflineRecognizerConfig config = new OfflineRecognizerConfig();
config.ModelConfig.Tokens = options.Tokens;
if (!String.IsNullOrEmpty(options.Encoder))
{
// this is a transducer model
config.ModelConfig.Transducer.Encoder = options.Encoder;
config.ModelConfig.Transducer.Decoder = options.Decoder;
config.ModelConfig.Transducer.Joiner = options.Joiner;
}
else if (!String.IsNullOrEmpty(options.Paraformer))
{
config.ModelConfig.Paraformer.Model = options.Paraformer;
}
else if (!String.IsNullOrEmpty(options.NeMoCtc))
{
config.ModelConfig.NeMoCtc.Model = options.NeMoCtc;
}
else
{
Console.WriteLine("Please provide a model");
return;
}
config.DecodingMethod = options.DecodingMethod;
config.MaxActivePaths = options.MaxActivePaths;
config.ModelConfig.Debug = 0;
OfflineRecognizer recognizer = new OfflineRecognizer(config);
string[] files = options.Files.ToArray();
// We create a separate stream for each file
List<OfflineStream> streams = new List<OfflineStream>();
streams.EnsureCapacity(files.Length);
for (int i = 0; i != files.Length; ++i)
{
OfflineStream s = recognizer.CreateStream();
WaveReader waveReader = new WaveReader(files[i]);
s.AcceptWaveform(waveReader.SampleRate, waveReader.Samples);
streams.Add(s);
}
recognizer.Decode(streams);
// display results
for (int i = 0; i != files.Length; ++i)
{
var text = streams[i].Result.Text;
Console.WriteLine("--------------------");
Console.WriteLine(files[i]);
Console.WriteLine(text);
}
Console.WriteLine("--------------------");
}
}

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dotnet-examples/offline-decode-files/WaveReader.cs Symbolic link
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../online-decode-files/WaveReader.cs

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dotnet-examples/offline-decode-files/offline-decode-files.csproj Normal file
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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net6.0</TargetFramework>
<RootNamespace>offline_decode_files</RootNamespace>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="CommandLineParser" Version="2.9.1" />
<PackageReference Include="org.k2fsa.sherpa.onnx" Version="*" />
</ItemGroup>
</Project>

16
dotnet-examples/offline-decode-files/run-nemo-ctc.sh Executable file
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#!/usr/bin/env bash
if [ ! -d ./sherpa-onnx-nemo-ctc-en-conformer-medium ]; then
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-nemo-ctc-en-conformer-medium
cd sherpa-onnx-nemo-ctc-en-conformer-medium
git lfs pull --include "*.onnx"
cd ..
fi
dotnet run \
--tokens=./sherpa-onnx-nemo-ctc-en-conformer-medium/tokens.txt \
--nemo-ctc=./sherpa-onnx-nemo-ctc-en-conformer-medium/model.onnx \
--num-threads=1 \
--files ./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/0.wav \
./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/1.wav \
./sherpa-onnx-nemo-ctc-en-conformer-medium/test_wavs/8k.wav

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dotnet-examples/offline-decode-files/run-paraformer.sh Executable file
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#!/usr/bin/env bash
if [ ! -d ./sherpa-onnx-paraformer-zh-2023-03-28 ]; then
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-paraformer-zh-2023-03-28
cd sherpa-onnx-paraformer-zh-2023-03-28
git lfs pull --include "*.onnx"
cd ..
fi
dotnet run \
--tokens=./sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt \
--paraformer=./sherpa-onnx-paraformer-zh-2023-03-28/model.onnx \
--num-threads=2 \
--files ./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/0.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/1.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/2.wav \
./sherpa-onnx-paraformer-zh-2023-03-28/test_wavs/8k.wav

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dotnet-examples/offline-decode-files/run-zipformer.sh Executable file
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#!/usr/bin/env bash
#
if [ ! -d ./sherpa-onnx-zipformer-en-2023-04-01 ]; then
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-zipformer-en-2023-04-01
cd sherpa-onnx-zipformer-en-2023-04-01
git lfs pull --include "*.onnx"
cd ..
fi
dotnet run \
--tokens=./sherpa-onnx-zipformer-en-2023-04-01/tokens.txt \
--encoder=./sherpa-onnx-zipformer-en-2023-04-01/encoder-epoch-99-avg-1.onnx \
--decoder=./sherpa-onnx-zipformer-en-2023-04-01/decoder-epoch-99-avg-1.onnx \
--joiner=./sherpa-onnx-zipformer-en-2023-04-01/joiner-epoch-99-avg-1.onnx \
--num-threads=2 \
--decoding-method=modified_beam_search \
--files ./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/0.wav \
./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/1.wav \
./sherpa-onnx-zipformer-en-2023-04-01/test_wavs/8k.wav

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dotnet-examples/online-decode-files/Program.cs Normal file
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// Copyright (c) 2023 Xiaomi Corporation
// Copyright (c) 2023 by manyeyes
//
// This file shows how to use a streaming model to decode files
// Please refer to
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html
// to download streaming models
using CommandLine.Text;
using CommandLine;
using SherpaOnnx;
using System.Collections.Generic;
using System.Linq;
using System;
class OnlineDecodeFiles
{
class Options
{
[Option(Required = true, HelpText = "Path to tokens.txt")]
public string Tokens { get; set; }
[Option(Required = true, HelpText = "Path to encoder.onnx")]
public string Encoder { get; set; }
[Option(Required = true, HelpText = "Path to decoder.onnx")]
public string Decoder { get; set; }
[Option(Required = true, HelpText = "Path to joiner.onnx")]
public string Joiner { get; set; }
[Option("num-threads", Required = false, Default = 1, HelpText = "Number of threads for computation")]
public int NumThreads { get; set; }
[Option("decoding-method", Required = false, Default = "greedy_search",
HelpText = "Valid decoding methods are: greedy_search, modified_beam_search")]
public string DecodingMethod { get; set; }
[Option(Required = false, Default = false, HelpText = "True to show model info during loading")]
public bool Debug { get; set; }
[Option("sample-rate", Required = false, Default = 16000, HelpText = "Sample rate of the data used to train the model")]
public int SampleRate { get; set; }
[Option("max-active-paths", Required = false, Default = 4,
HelpText = @"Used only when --decoding--method is modified_beam_search.
It specifies number of active paths to keep during the search")]
public int MaxActivePaths { get; set; }
[Option("enable-endpoint", Required = false, Default = false,
HelpText = "True to enable endpoint detection.")]
public bool EnableEndpoint { get; set; }
[Option("rule1-min-trailing-silence", Required = false, Default = 2.4F,
HelpText = @"An endpoint is detected if trailing silence in seconds is
larger than this value even if nothing has been decoded. Used only when --enable-endpoint is true.")]
public float Rule1MinTrailingSilence { get; set; }
[Option("rule2-min-trailing-silence", Required = false, Default = 1.2F,
HelpText = @"An endpoint is detected if trailing silence in seconds is
larger than this value after something that is not blank has been decoded. Used
only when --enable-endpoint is true.")]
public float Rule2MinTrailingSilence { get; set; }
[Option("rule3-min-utterance-length", Required = false, Default = 20.0F,
HelpText = @"An endpoint is detected if the utterance in seconds is
larger than this value. Used only when --enable-endpoint is true.")]
public float Rule3MinUtteranceLength { get; set; }
[Option("files", Required = true, HelpText = "Audio files for decoding")]
public IEnumerable<string> Files { get; set; }
}
static void Main(string[] args)
{
var parser = new CommandLine.Parser(with => with.HelpWriter = null);
var parserResult = parser.ParseArguments<Options>(args);
parserResult
.WithParsed<Options>(options => Run(options))
.WithNotParsed(errs => DisplayHelp(parserResult, errs));
}
private static void DisplayHelp<T>(ParserResult<T> result, IEnumerable<Error> errs)
{
string usage = @"
dotnet run \
--tokens=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt \
--encoder=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx \
--decoder=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx \
--joiner=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx \
--num-threads=2 \
--decoding-method=modified_beam_search \
--debug=false \
./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/0.wav \
./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/1.wav
Please refer to
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html
to download pre-trained streaming models.
";
var helpText = HelpText.AutoBuild(result, h =>
{
h.AdditionalNewLineAfterOption = false;
h.Heading = usage;
h.Copyright = "Copyright (c) 2023 Xiaomi Corporation";
return HelpText.DefaultParsingErrorsHandler(result, h);
}, e => e);
Console.WriteLine(helpText);
}
private static void Run(Options options)
{
OnlineRecognizerConfig config = new OnlineRecognizerConfig();
config.FeatConfig.SampleRate = options.SampleRate;
// All models from icefall using feature dim 80.
// You can change it if your model has a different feature dim.
config.FeatConfig.FeatureDim = 80;
config.TransducerModelConfig.Encoder = options.Encoder;
config.TransducerModelConfig.Decoder = options.Decoder;
config.TransducerModelConfig.Joiner = options.Joiner;
config.TransducerModelConfig.Tokens = options.Tokens;
config.TransducerModelConfig.NumThreads = options.NumThreads;
config.TransducerModelConfig.Debug = options.Debug ? 1 : 0;
config.DecodingMethod = options.DecodingMethod;
config.MaxActivePaths = options.MaxActivePaths;
config.EnableEndpoint = options.EnableEndpoint ? 1 : 0;
config.Rule1MinTrailingSilence = options.Rule1MinTrailingSilence;
config.Rule2MinTrailingSilence = options.Rule2MinTrailingSilence;
config.Rule3MinUtteranceLength = options.Rule3MinUtteranceLength;
OnlineRecognizer recognizer = new OnlineRecognizer(config);
string[] files = options.Files.ToArray();
// We create a separate stream for each file
List<OnlineStream> streams = new List<OnlineStream>();
streams.EnsureCapacity(files.Length);
for (int i = 0; i != files.Length; ++i)
{
OnlineStream s = recognizer.CreateStream();
WaveReader waveReader = new WaveReader(files[i]);
s.AcceptWaveform(waveReader.SampleRate, waveReader.Samples);
float[] tailPadding = new float[(int)(waveReader.SampleRate * 0.3)];
s.AcceptWaveform(waveReader.SampleRate, tailPadding);
s.InputFinished();
streams.Add(s);
}
while (true)
{
var readyStreams = streams.Where(s => recognizer.IsReady(s));
if (!readyStreams.Any())
{
break;
}
recognizer.Decode(readyStreams);
}
// display results
for (int i = 0; i != files.Length; ++i)
{
var text = recognizer.GetResult(streams[i]).Text;
Console.WriteLine("--------------------");
Console.WriteLine(files[i]);
Console.WriteLine(text);
}
Console.WriteLine("--------------------");
}
}

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dotnet-examples/online-decode-files/WaveReader.cs Normal file
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// Copyright (c) 2023 Xiaomi Corporation (authors: Fangjun Kuang)
using System;
using System.IO;
using System.Runtime.InteropServices;
namespace SherpaOnnx
{
[StructLayout(LayoutKind.Sequential)]
public struct WaveHeader
{
public Int32 ChunkID;
public Int32 ChunkSize;
public Int32 Format;
public Int32 SubChunk1ID;
public Int32 SubChunk1Size;
public Int16 AudioFormat;
public Int16 NumChannels;
public Int32 SampleRate;
public Int32 ByteRate;
public Int16 BlockAlign;
public Int16 BitsPerSample;
public Int32 SubChunk2ID;
public Int32 SubChunk2Size;
public bool Validate()
{
if (ChunkID != 0x46464952)
{
Console.WriteLine($"Invalid chunk ID: 0x{ChunkID:X}. Expect 0x46464952");
return false;
}
// E V A W
if (Format != 0x45564157)
{
Console.WriteLine($"Invalid format: 0x{Format:X}. Expect 0x45564157");
return false;
}
// t m f
if (SubChunk1ID != 0x20746d66)
{
Console.WriteLine($"Invalid SubChunk1ID: 0x{SubChunk1ID:X}. Expect 0x20746d66");
return false;
}
if (SubChunk1Size != 16)
{
Console.WriteLine($"Invalid SubChunk1Size: {SubChunk1Size}. Expect 16");
return false;
}
if (AudioFormat != 1)
{
Console.WriteLine($"Invalid AudioFormat: {AudioFormat}. Expect 1");
return false;
}
if (NumChannels != 1)
{
Console.WriteLine($"Invalid NumChannels: {NumChannels}. Expect 1");
return false;
}
if (ByteRate != (SampleRate * NumChannels * BitsPerSample / 8))
{
Console.WriteLine($"Invalid byte rate: {ByteRate}.");
return false;
}
if (BlockAlign != (NumChannels * BitsPerSample / 8))
{
Console.WriteLine($"Invalid block align: {ByteRate}.");
return false;
}
if (BitsPerSample != 16)
{ // we support only 16 bits per sample
Console.WriteLine($"Invalid bits per sample: {BitsPerSample}. Expect 16");
return false;
}
return true;
}
}
// It supports only 16-bit, single channel WAVE format.
// The sample rate can be any value.
public class WaveReader
{
public WaveReader(String fileName)
{
if (!File.Exists(fileName))
{
throw new ApplicationException($"{fileName} does not exist!");
}
using (var stream = File.Open(fileName, FileMode.Open))
{
using (var reader = new BinaryReader(stream))
{
_header = ReadHeader(reader);
if (!_header.Validate())
{
throw new ApplicationException($"Invalid wave file ${fileName}");
}
SkipMetaData(reader);
// now read samples
// _header.SubChunk2Size contains number of bytes in total.
// we assume each sample is of type int16
byte[] buffer = reader.ReadBytes(_header.SubChunk2Size);
short[] samples_int16 = new short[_header.SubChunk2Size / 2];
Buffer.BlockCopy(buffer, 0, samples_int16, 0, buffer.Length);
_samples = new float[samples_int16.Length];
for (var i = 0; i < samples_int16.Length; ++i)
{
_samples[i] = samples_int16[i] / 32768.0F;
}
}
}
}
private static WaveHeader ReadHeader(BinaryReader reader)
{
byte[] bytes = reader.ReadBytes(Marshal.SizeOf(typeof(WaveHeader)));
GCHandle handle = GCHandle.Alloc(bytes, GCHandleType.Pinned);
WaveHeader header = (WaveHeader)Marshal.PtrToStructure(handle.AddrOfPinnedObject(), typeof(WaveHeader))!;
handle.Free();
return header;
}
private void SkipMetaData(BinaryReader reader)
{
var bs = reader.BaseStream;
Int32 subChunk2ID = _header.SubChunk2ID;
Int32 subChunk2Size = _header.SubChunk2Size;
while (bs.Position != bs.Length && subChunk2ID != 0x61746164)
{
bs.Seek(subChunk2Size, SeekOrigin.Current);
subChunk2ID = reader.ReadInt32();
subChunk2Size = reader.ReadInt32();
}
_header.SubChunk2ID = subChunk2ID;
_header.SubChunk2Size = subChunk2Size;
}
private WaveHeader _header;
// Samples are normalized to the range [-1, 1]
private float[] _samples;
public int SampleRate => _header.SampleRate;
public float[] Samples => _samples;
public static void Test(String fileName)
{
WaveReader reader = new WaveReader(fileName);
Console.WriteLine($"samples length: {reader.Samples.Length}");
Console.WriteLine($"samples rate: {reader.SampleRate}");
}
}
}

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dotnet-examples/online-decode-files/online-decode-files.csproj Normal file
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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net6.0</TargetFramework>
<RootNamespace>online_decode_files</RootNamespace>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="CommandLineParser" Version="2.9.1" />
<PackageReference Include="org.k2fsa.sherpa.onnx" Version="*" />
</ItemGroup>
</Project>

21
dotnet-examples/online-decode-files/run.sh Executable file
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#!/usr/bin/env bash
# Please refer to
# https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english
# to download the model files
if [ ! -d ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 ]; then
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20
cd sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20
git lfs pull --include "*.onnx"
cd ..
fi
dotnet run -c Release \
--tokens ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt \
--encoder ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.int8.onnx \
--decoder ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.int8.onnx \
--joiner ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.int8.onnx \
--decoding-method greedy_search \
--files ./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/1.wav \
./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/0.wav \

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dotnet-examples/sherpa-onnx.sln Normal file
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