63 lines
2.2 KiB
C#
63 lines
2.2 KiB
C#
// Copyright (c) 2024 Xiaomi Corporation
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//
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// This file shows how to use a silero_vad model with a non-streaming Paraformer
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// for speech recognition.
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using SherpaOnnx;
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using System.Collections.Generic;
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using System;
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class VadNonStreamingAsrParaformer
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{
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static void Main(string[] args)
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{
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// please download model files from
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// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
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OfflineRecognizerConfig config = new OfflineRecognizerConfig();
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config.ModelConfig.Paraformer.Model = "./sherpa-onnx-paraformer-zh-2023-03-28/model.int8.onnx";
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config.ModelConfig.Tokens = "./sherpa-onnx-paraformer-zh-2023-03-28/tokens.txt";
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config.ModelConfig.Debug = 0;
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OfflineRecognizer recognizer = new OfflineRecognizer(config);
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VadModelConfig vadModelConfig = new VadModelConfig();
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vadModelConfig.SileroVad.Model = "./silero_vad.onnx";
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vadModelConfig.Debug = 0;
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VoiceActivityDetector vad = new VoiceActivityDetector(vadModelConfig, 60);
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string testWaveFilename = "./lei-jun-test.wav";
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WaveReader reader = new WaveReader(testWaveFilename);
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int numSamples = reader.Samples.Length;
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int windowSize = vadModelConfig.SileroVad.WindowSize;
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int sampleRate = vadModelConfig.SampleRate;
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int numIter = numSamples / windowSize;
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for (int i = 0; i != numIter; ++i) {
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int start = i * windowSize;
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float[] samples = new float[windowSize];
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Array.Copy(reader.Samples, start, samples, 0, windowSize);
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vad.AcceptWaveform(samples);
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if (vad.IsSpeechDetected()) {
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while (!vad.IsEmpty()) {
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SpeechSegment segment = vad.Front();
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float startTime = segment.Start / (float)sampleRate;
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float duration = segment.Samples.Length / (float)sampleRate;
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OfflineStream stream = recognizer.CreateStream();
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stream.AcceptWaveform(sampleRate, segment.Samples);
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recognizer.Decode(stream);
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String text = stream.Result.Text;
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if (!String.IsNullOrEmpty(text)) {
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Console.WriteLine("{0}--{1}: {2}", String.Format("{0:0.00}", startTime),
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String.Format("{0:0.00}", startTime+duration), text);
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}
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vad.Pop();
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}
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}
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}
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}
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}
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