/// <summary>
/// Based on article: http://mziccard.me/2015/05/28/beats-detection-algorithms-1/
/// </summary>
/// <param name="values"></param>
private eRecognitionStatus Recognize(double[] values) // ORG: PlotSignal()
{
eRecognitionStatus recognitionStatus = eRecognitionStatus.UnRecognized;
double energySum = CalculateEnergy(values);
// We let the blocks list number grow to collect better statistical information.
if (mEnergyForBlocksList.Count > 900)
{
double avgEnergy = mEnergyForBlocksList.Sum() / mEnergyForBlocksList.Count;
double varianceEnergy = CalculateVariance(avgEnergy);
//double factorC = -0.0025714 * varianceEnergy + 1.5142857; // this is the factorC from the original artical (not the same one as in the article above)
double factorC = -0.0000015 * varianceEnergy + 1.5142857; // this is the factorC we were using with the earlier records
// In that case, pop is recognized.
if (energySum > factorC * avgEnergy)
{
if (mSampleCount % 5 == 0)
{
mRecordInfoDescriptor.AddRecognitionTime(mStopwatch.ElapsedMilliseconds / 1000.0);
recognitionStatus = eRecognitionStatus.Recognized;
}
}
mSampleCount++;
}
//new improvement:
// Adds use only the first 2000 blocks, in order to reduce the influence of the many pops at the peak,
// because when getting around 3000-3500 blocks, a small pop is to close to the avarage.
if (mEnergyForBlocksList.Count < 2000)
{
mEnergyForBlocksList.Add(energySum);
}
/// Every <see cref="mIntervalsInSeconds"/> seconds sending test object to the KNN tester.
if (mStopwatch.IsRunning && (mStopwatch.ElapsedMilliseconds / 1000.0) > 4 * mIntervalsInSeconds)
{
mIntervalsInSeconds++;
mRecordInfoDescriptor.UpdateDurationAndLastSection(mStopwatch.ElapsedMilliseconds / 1000.0);
RecordNeighbor testObject = mKnnTester.GenerateNeighborFromRecordInfoDescriptor(mRecordInfoDescriptor);
if (mKnnTester.TestAndClassify(testObject, KNN_PARAMETER) == classificationA)
{
Stop("Recognizer detected that the popcorn is ready");
}
}
return(recognitionStatus);
}
private eRecognitionStatus Recognize()
{
eRecognitionStatus recognitionStatus = eRecognitionStatus.UnRecognized;
if (mSubSoundsQueue.Count != 0)
{
IAudioFile subSound = mSubSoundsQueue.Dequeue();
bool isMatchFound = mSoundFingerprintingUtility.IsAudioFileDetected(
subSound,
mAmplification,
mSecondsToAnalyzeAudioFiles);
if (isMatchFound)
{
recognitionStatus = eRecognitionStatus.Recognized;
}
}
return(recognitionStatus);
}
private eRecognitionStatus Recognize()
{
eRecognitionStatus recognitionStatus = eRecognitionStatus.UnRecognized;
if (mSubSoundsQueue.Count != 0)
{
IAudioFile subSound = mSubSoundsQueue.Dequeue();
bool isMatchFound = SoundFingerprintingWrapper.FindMatchesForAudioFile(
subSound,
mAmplification,
mSecondsToAnalyzeAudioFiles);
if (isMatchFound)
{
recognitionStatus = eRecognitionStatus.Recognized;
SoundFingerprintingWrapper.StoreNewAudioFileData(subSound);
}
}
return(recognitionStatus);
}
