Refactor C# code and support building nuget packages for cross-platforms (#144)
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Fangjun Kuang
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dotnet-examples/online-decode-files/Program.cs
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181
dotnet-examples/online-decode-files/Program.cs
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// Copyright (c) 2023 Xiaomi Corporation
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// Copyright (c) 2023 by manyeyes
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//
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// This file shows how to use a streaming model to decode files
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// Please refer to
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// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html
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// to download streaming models
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using CommandLine.Text;
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using CommandLine;
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using SherpaOnnx;
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using System.Collections.Generic;
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using System.Linq;
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using System;
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class OnlineDecodeFiles
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{
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class Options
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{
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[Option(Required = true, HelpText = "Path to tokens.txt")]
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public string Tokens { get; set; }
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[Option(Required = true, HelpText = "Path to encoder.onnx")]
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public string Encoder { get; set; }
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[Option(Required = true, HelpText = "Path to decoder.onnx")]
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public string Decoder { get; set; }
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[Option(Required = true, HelpText = "Path to joiner.onnx")]
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public string Joiner { get; set; }
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[Option("num-threads", Required = false, Default = 1, HelpText = "Number of threads for computation")]
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public int NumThreads { get; set; }
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[Option("decoding-method", Required = false, Default = "greedy_search",
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HelpText = "Valid decoding methods are: greedy_search, modified_beam_search")]
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public string DecodingMethod { get; set; }
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[Option(Required = false, Default = false, HelpText = "True to show model info during loading")]
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public bool Debug { get; set; }
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[Option("sample-rate", Required = false, Default = 16000, HelpText = "Sample rate of the data used to train the model")]
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public int SampleRate { get; set; }
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[Option("max-active-paths", Required = false, Default = 4,
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HelpText = @"Used only when --decoding--method is modified_beam_search.
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It specifies number of active paths to keep during the search")]
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public int MaxActivePaths { get; set; }
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[Option("enable-endpoint", Required = false, Default = false,
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HelpText = "True to enable endpoint detection.")]
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public bool EnableEndpoint { get; set; }
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[Option("rule1-min-trailing-silence", Required = false, Default = 2.4F,
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HelpText = @"An endpoint is detected if trailing silence in seconds is
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larger than this value even if nothing has been decoded. Used only when --enable-endpoint is true.")]
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public float Rule1MinTrailingSilence { get; set; }
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[Option("rule2-min-trailing-silence", Required = false, Default = 1.2F,
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HelpText = @"An endpoint is detected if trailing silence in seconds is
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larger than this value after something that is not blank has been decoded. Used
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only when --enable-endpoint is true.")]
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public float Rule2MinTrailingSilence { get; set; }
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[Option("rule3-min-utterance-length", Required = false, Default = 20.0F,
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HelpText = @"An endpoint is detected if the utterance in seconds is
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larger than this value. Used only when --enable-endpoint is true.")]
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public float Rule3MinUtteranceLength { get; set; }
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[Option("files", Required = true, HelpText = "Audio files for decoding")]
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public IEnumerable<string> Files { get; set; }
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}
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static void Main(string[] args)
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{
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var parser = new CommandLine.Parser(with => with.HelpWriter = null);
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var parserResult = parser.ParseArguments<Options>(args);
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parserResult
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.WithParsed<Options>(options => Run(options))
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.WithNotParsed(errs => DisplayHelp(parserResult, errs));
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}
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private static void DisplayHelp<T>(ParserResult<T> result, IEnumerable<Error> errs)
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{
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string usage = @"
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dotnet run \
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--tokens=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/tokens.txt \
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--encoder=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/encoder-epoch-99-avg-1.onnx \
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--decoder=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/decoder-epoch-99-avg-1.onnx \
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--joiner=./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/joiner-epoch-99-avg-1.onnx \
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--num-threads=2 \
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--decoding-method=modified_beam_search \
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--debug=false \
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./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/0.wav \
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./sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20/test_wavs/1.wav
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Please refer to
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https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html
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to download pre-trained streaming models.
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";
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var helpText = HelpText.AutoBuild(result, h =>
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{
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h.AdditionalNewLineAfterOption = false;
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h.Heading = usage;
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h.Copyright = "Copyright (c) 2023 Xiaomi Corporation";
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return HelpText.DefaultParsingErrorsHandler(result, h);
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}, e => e);
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Console.WriteLine(helpText);
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}
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private static void Run(Options options)
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{
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OnlineRecognizerConfig config = new OnlineRecognizerConfig();
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config.FeatConfig.SampleRate = options.SampleRate;
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// All models from icefall using feature dim 80.
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// You can change it if your model has a different feature dim.
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config.FeatConfig.FeatureDim = 80;
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config.TransducerModelConfig.Encoder = options.Encoder;
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config.TransducerModelConfig.Decoder = options.Decoder;
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config.TransducerModelConfig.Joiner = options.Joiner;
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config.TransducerModelConfig.Tokens = options.Tokens;
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config.TransducerModelConfig.NumThreads = options.NumThreads;
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config.TransducerModelConfig.Debug = options.Debug ? 1 : 0;
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config.DecodingMethod = options.DecodingMethod;
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config.MaxActivePaths = options.MaxActivePaths;
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config.EnableEndpoint = options.EnableEndpoint ? 1 : 0;
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config.Rule1MinTrailingSilence = options.Rule1MinTrailingSilence;
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config.Rule2MinTrailingSilence = options.Rule2MinTrailingSilence;
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config.Rule3MinUtteranceLength = options.Rule3MinUtteranceLength;
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OnlineRecognizer recognizer = new OnlineRecognizer(config);
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string[] files = options.Files.ToArray();
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// We create a separate stream for each file
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List<OnlineStream> streams = new List<OnlineStream>();
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streams.EnsureCapacity(files.Length);
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for (int i = 0; i != files.Length; ++i)
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{
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OnlineStream s = recognizer.CreateStream();
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WaveReader waveReader = new WaveReader(files[i]);
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s.AcceptWaveform(waveReader.SampleRate, waveReader.Samples);
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float[] tailPadding = new float[(int)(waveReader.SampleRate * 0.3)];
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s.AcceptWaveform(waveReader.SampleRate, tailPadding);
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s.InputFinished();
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streams.Add(s);
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}
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while (true)
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{
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var readyStreams = streams.Where(s => recognizer.IsReady(s));
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if (!readyStreams.Any())
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{
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break;
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}
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recognizer.Decode(readyStreams);
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}
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// display results
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for (int i = 0; i != files.Length; ++i)
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{
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var text = recognizer.GetResult(streams[i]).Text;
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Console.WriteLine("--------------------");
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Console.WriteLine(files[i]);
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Console.WriteLine(text);
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}
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Console.WriteLine("--------------------");
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}
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}
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