public void TestFeatureUtility()
{
var arraySoundSignalReader = new ArraySignalReader(new float[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 });
var filteredSignal = new PreemphasisFilter(arraySoundSignalReader, 0.95f);
VoiceActivitySignalReader fu = new VoiceActivitySignalReader(filteredSignal, 5);
float[] frame1;
float[] frame2;
float[] frame3;
bool isVoice;
fu.Read( 5, 2, out frame1,out isVoice);
fu.Read(5, 2, out frame2, out isVoice);
fu.Read(5, 2, out frame3, out isVoice);
var arraySoundSignalReader1 = new ArraySignalReader(new float[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 });
var filteredSignal1 = new PreemphasisFilter(arraySoundSignalReader1, 0.95f);
float[] frame4 = new float[5];
float[] frame5 = new float[5];
//float[] frame6 = new float[5];
filteredSignal1.Read(frame4, 0, 5);
filteredSignal1.Read(frame5, 0, 5);
}
private void ExtractFeaturesInternalUsingVad(ISoundSignalReader signal, Action<List<double[]>> featureExtracted,
SignalVisitor voiceVisitor)
{
var featureProvider = FeaturesProviderFactory.GetProvider(ProviderParameters, signal);
var frameSize = (int) Math.Floor(signal.SampleRate*FrameSizeMiliseconds/1000.0);
var stepSize = (int) Math.Floor(signal.SampleRate*StepSizeMiliseconds/1000.0);
var filteredSignal = new PreemphasisFilter(signal, 0.95f);
float[] frame;
var voiceStream = new VoiceActivitySignalReader(filteredSignal, frameSize, 8);
if (voiceVisitor != null)
{
voiceStream.Accept(voiceVisitor);
}
int index = 0, silentSamples = 0, noOfItems = ProviderParameters.NumberOfCoeff - 1;
var observables = new List<double[]>();
bool isVoice;
while (voiceStream.Read(frameSize, stepSize, out frame, out isVoice))
{
if (isVoice)
{
bool isEmpty;
var features = featureProvider.Extract(frame, out isEmpty);
silentSamples = 0;
observables.Add(features);
if (featureProvider.ComputeDelta)
{
ComputeDelta(observables, index - 1, 1, noOfItems);
ComputeDelta(observables, index - 2, noOfItems + 1, noOfItems, true);
}
index++;
}
else if (observables.Count > 0 && silentSamples > SilenceThreshHold)
{
if (index >= MinWordLength)
{
if (featureProvider.ComputeDelta)
{
ComputeDelta(observables, index - 1, 1, noOfItems);
ComputeDelta(observables, index - 2, noOfItems + 1, noOfItems, true);
ComputeDelta(observables, index - 1, noOfItems + 1, noOfItems, true);
}
featureExtracted(observables);
}
observables = new List<double[]>();
index = 0;
}
else
{
silentSamples++;
}
}
}