EngineX-Iluvatar/enginex-mr_series-sherpa-onnx
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Upgraded to .NET 8 and made code style a little more internally consistent. (#1680)

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This commit is contained in:
Michael Lamothe
2025-01-04 19:39:06 +11:00
committed by GitHub
parent bf3330c906
commit 8a60985363
29 changed files with 354 additions and 404 deletions
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71
dotnet-examples/offline-decode-files/Program.cs
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@@ -5,17 +5,14 @@
// 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 CommandLine.Text;
using SherpaOnnx;
using System.Collections.Generic;
using System;
class OfflineDecodeFiles
{
class Options
{
[Option("sample-rate", Required = false, Default = 16000, HelpText = "Sample rate of the data used to train the model")]
public int SampleRate { get; set; } = 16000;
@@ -23,58 +20,58 @@ class OfflineDecodeFiles
public int FeatureDim { get; set; } = 80;
[Option(Required = false, HelpText = "Path to tokens.txt")]
public string Tokens { get; set; } = "";
public string Tokens { get; set; } = string.Empty;
[Option(Required = false, Default = "", HelpText = "Path to transducer encoder.onnx. Used only for transducer models")]
public string Encoder { get; set; } = "";
public string Encoder { get; set; } = string.Empty;
[Option(Required = false, Default = "", HelpText = "Path to transducer decoder.onnx. Used only for transducer models")]
public string Decoder { get; set; } = "";
public string Decoder { get; set; } = string.Empty;
[Option(Required = false, Default = "", HelpText = "Path to transducer joiner.onnx. Used only for transducer models")]
public string Joiner { get; set; } = "";
public string Joiner { get; set; } = string.Empty;
[Option("model-type", Required = false, Default = "", HelpText = "model type")]
public string ModelType { get; set; } = "";
public string ModelType { get; set; } = string.Empty;
[Option("whisper-encoder", Required = false, Default = "", HelpText = "Path to whisper encoder.onnx. Used only for whisper models")]
public string WhisperEncoder { get; set; } = "";
public string WhisperEncoder { get; set; } = string.Empty;
[Option("whisper-decoder", Required = false, Default = "", HelpText = "Path to whisper decoder.onnx. Used only for whisper models")]
public string WhisperDecoder { get; set; } = "";
public string WhisperDecoder { get; set; } = string.Empty;
[Option("whisper-language", Required = false, Default = "", HelpText = "Language of the input file. Can be empty")]
public string WhisperLanguage { get; set; } = "";
public string WhisperLanguage { get; set; } = string.Empty;
[Option("whisper-task", Required = false, Default = "transcribe", HelpText = "transcribe or translate")]
public string WhisperTask { get; set; } = "transcribe";
[Option("moonshine-preprocessor", Required = false, Default = "", HelpText = "Path to preprocess.onnx. Used only for Moonshine models")]
public string MoonshinePreprocessor { get; set; } = "";
public string MoonshinePreprocessor { get; set; } = string.Empty;
[Option("moonshine-encoder", Required = false, Default = "", HelpText = "Path to encode.onnx. Used only for Moonshine models")]
public string MoonshineEncoder { get; set; } = "";
public string MoonshineEncoder { get; set; } = string.Empty;
[Option("moonshine-uncached-decoder", Required = false, Default = "", HelpText = "Path to uncached_decode.onnx. Used only for Moonshine models")]
public string MoonshineUncachedDecoder { get; set; } = "";
public string MoonshineUncachedDecoder { get; set; } = string.Empty;
[Option("moonshine-cached-decoder", Required = false, Default = "", HelpText = "Path to cached_decode.onnx. Used only for Moonshine models")]
public string MoonshineCachedDecoder { get; set; } = "";
public string MoonshineCachedDecoder { get; set; } = string.Empty;
[Option("tdnn-model", Required = false, Default = "", HelpText = "Path to tdnn yesno model")]
public string TdnnModel { get; set; } = "";
public string TdnnModel { get; set; } = string.Empty;
[Option(Required = false, HelpText = "Path to model.onnx. Used only for paraformer models")]
public string Paraformer { get; set; } = "";
public string Paraformer { get; set; } = string.Empty;
[Option("nemo-ctc", Required = false, HelpText = "Path to model.onnx. Used only for NeMo CTC models")]
public string NeMoCtc { get; set; } = "";
public string NeMoCtc { get; set; } = string.Empty;
[Option("telespeech-ctc", Required = false, HelpText = "Path to model.onnx. Used only for TeleSpeech CTC models")]
public string TeleSpeechCtc { get; set; } = "";
public string TeleSpeechCtc { get; set; } = string.Empty;
[Option("sense-voice-model", Required = false, HelpText = "Path to model.onnx. Used only for SenseVoice CTC models")]
public string SenseVoiceModel { get; set; } = "";
public string SenseVoiceModel { get; set; } = string.Empty;
[Option("sense-voice-use-itn", Required = false, HelpText = "1 to use inverse text normalization for sense voice.")]
public int SenseVoiceUseItn { get; set; } = 1;
@@ -88,7 +85,7 @@ class OfflineDecodeFiles
[Option("rule-fsts", Required = false, Default = "",
HelpText = "If not empty, path to rule fst for inverse text normalization")]
public string RuleFsts { get; set; } = "";
public string RuleFsts { get; set; } = string.Empty;
[Option("max-active-paths", Required = false, Default = 4,
HelpText = @"Used only when --decoding--method is modified_beam_search.
@@ -96,7 +93,7 @@ It specifies number of active paths to keep during the search")]
public int MaxActivePaths { get; set; } = 4;
[Option("hotwords-file", Required = false, Default = "", HelpText = "Path to hotwords.txt")]
public string HotwordsFile { get; set; } = "";
public string HotwordsFile { get; set; } = string.Empty;
[Option("hotwords-score", Required = false, Default = 1.5F, HelpText = "hotwords score")]
public float HotwordsScore { get; set; } = 1.5F;
@@ -117,7 +114,7 @@ It specifies number of active paths to keep during the search")]
private static void DisplayHelp<T>(ParserResult<T> result, IEnumerable<Error> errs)
{
string usage = @"
var usage = @"
# Zipformer
dotnet run \
@@ -213,42 +210,42 @@ to download pre-trained Tdnn models.
config.ModelConfig.Tokens = options.Tokens;
if (!String.IsNullOrEmpty(options.Encoder))
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))
else if (!string.IsNullOrEmpty(options.Paraformer))
{
config.ModelConfig.Paraformer.Model = options.Paraformer;
}
else if (!String.IsNullOrEmpty(options.NeMoCtc))
else if (!string.IsNullOrEmpty(options.NeMoCtc))
{
config.ModelConfig.NeMoCtc.Model = options.NeMoCtc;
}
else if (!String.IsNullOrEmpty(options.TeleSpeechCtc))
else if (!string.IsNullOrEmpty(options.TeleSpeechCtc))
{
config.ModelConfig.TeleSpeechCtc = options.TeleSpeechCtc;
}
else if (!String.IsNullOrEmpty(options.WhisperEncoder))
else if (!string.IsNullOrEmpty(options.WhisperEncoder))
{
config.ModelConfig.Whisper.Encoder = options.WhisperEncoder;
config.ModelConfig.Whisper.Decoder = options.WhisperDecoder;
config.ModelConfig.Whisper.Language = options.WhisperLanguage;
config.ModelConfig.Whisper.Task = options.WhisperTask;
}
else if (!String.IsNullOrEmpty(options.TdnnModel))
else if (!string.IsNullOrEmpty(options.TdnnModel))
{
config.ModelConfig.Tdnn.Model = options.TdnnModel;
}
else if (!String.IsNullOrEmpty(options.SenseVoiceModel))
else if (!string.IsNullOrEmpty(options.SenseVoiceModel))
{
config.ModelConfig.SenseVoice.Model = options.SenseVoiceModel;
config.ModelConfig.SenseVoice.UseInverseTextNormalization = options.SenseVoiceUseItn;
}
else if (!String.IsNullOrEmpty(options.MoonshinePreprocessor))
else if (!string.IsNullOrEmpty(options.MoonshinePreprocessor))
{
config.ModelConfig.Moonshine.Preprocessor = options.MoonshinePreprocessor;
config.ModelConfig.Moonshine.Encoder = options.MoonshineEncoder;
@@ -270,17 +267,17 @@ to download pre-trained Tdnn models.
config.ModelConfig.Debug = 0;
OfflineRecognizer recognizer = new OfflineRecognizer(config);
var recognizer = new OfflineRecognizer(config);
string[] files = options.Files.ToArray();
var files = options.Files.ToArray();
// We create a separate stream for each file
List<OfflineStream> streams = new List<OfflineStream>();
var streams = new List<OfflineStream>();
streams.EnsureCapacity(files.Length);
for (int i = 0; i != files.Length; ++i)
{
OfflineStream s = recognizer.CreateStream();
var s = recognizer.CreateStream();
WaveReader waveReader = new WaveReader(files[i]);
s.AcceptWaveform(waveReader.SampleRate, waveReader.Samples);
@@ -299,7 +296,7 @@ to download pre-trained Tdnn models.
Console.WriteLine("Tokens: [{0}]", string.Join(", ", r.Tokens));
if (r.Timestamps != null && r.Timestamps.Length > 0) {
Console.Write("Timestamps: [");
var sep = "";
var sep = string.Empty;
for (int k = 0; k != r.Timestamps.Length; ++k)
{
Console.Write("{0}{1}", sep, r.Timestamps[k].ToString("0.00"));