private void StartStopRecognition(object sender, RoutedEventArgs e)
{
if (_currentState == AppState.Idle)
{
txtRecognizedText.Text = string.Empty;
var recognitionEngine = new DetectionEngine(_codebook, _models);
_signal = new MicrophoneSoundSignalReader();
var length = (_signal.SampleRate / 1000.0) * EngineParameters.Default.StepSizeMiliseconds;
if (_aggregator != null)
{
_aggregator.SampleReady -= AggregatorSampleReady;
}
_aggregator = new SampleAggregator(Convert.ToInt32(length));
_aggregator.SampleReady += AggregatorSampleReady;
_signal.Start();
Action action = () =>
{
Thread.Sleep(3000);
recognitionEngine.RecognizeAsync(_signal, OnMessageReceived, _aggregator);
};
action.BeginInvoke(null, null);
btnRecog.Content = "Stop Recognition";
_currentState = AppState.Recognition;
}
else
{
btnRecog.Content = "Start Recognition";
_signal.Close();
_currentState = AppState.Idle;
_aggregator.SampleReady -= AggregatorSampleReady;
_aggregator = null;
}
}
public TrainResult Train(Dictionary<string, IList<ISoundSignalReader>> signalsDictionary,
SampleAggregator aggregator = null)
{
Parallel.ForEach(signalsDictionary, item =>
{
BuildModel(item.Value, item.Key, aggregator);
});
return new TrainResult { Catalog = _codeBook, Models = _models.Values.ToArray() };
}
private void AggregatorSampleReady(object sender, SampleAggregator.SamplePointEventArgs e)
{
renderer.AddValue(e.Point);
}
public void AddValue(SampleAggregator.SamplePoint samplePoint)
{
_queue.Enqueue(samplePoint);
var action = new Action(Refresh);
Dispatcher.BeginInvoke(action, DispatcherPriority.Render);
}
