/// <summary>
/// Implements the "Adaptive Level Equalisatsion" algorithm of Lamel et al, 1981 - with modifications for our signals.
/// Units are assumed to be decibels.
/// Returns the min and max frame dB AND the estimate MODAL or BACKGROUND noise for the signal array
/// IF This modal noise is subtracted from each frame dB, the effect is to set set average background noise level = 0 dB.
/// The algorithm is described in Lamel et al, 1981.
/// USED TO SEGMENT A RECORDING INTO SILENCE AND VOCALISATION
/// NOTE: noiseThreshold is passed as decibels. Original Lamel algorithm ONLY SEARCHES in range min to 10dB above min.
///
/// This method debugged on 7 Aug 2018 using following command line arguments:
/// audio2csv Y:\TheNatureConservency\Myanmar\20180517\site112\2018_02_14_Bar5\20180214_Bar5\20180214_101121_Bar5.wav Towsey.Acoustic.yml C:\Temp... -m True
/// </summary>
/// <param name="dBarray">signal in decibel values</param>
/// <param name="minDb">minimum value in the passed array of decibel values</param>
/// <param name="maxDb">maximum value in the passed array of decibel values</param>
/// <param name="modeNoise">modal or background noise in decibels</param>
/// <param name="sdNoise">estimated sd of the noies - assuming noise to be guassian</param>
public static void CalculateNoiseUsingLamelsAlgorithm(
double[] dBarray,
out double minDb,
out double maxDb,
out double modeNoise,
out double sdNoise)
{
// set constants
double noiseThreshold_DB = 10.0; // dB
var binCount = 100; // number of bins for histogram is FIXED
double histogramBinWidth = noiseThreshold_DB / binCount;
//ignore first N and last N frames when calculating background noise level because
// sometimes these frames have atypically low signal values
int buffer = 20; //ignore first N and last N frames when calculating background noise level
//HOWEVER do not ignore them for short recordings!
int arrayLength = dBarray.Length;
if (arrayLength < 1000)
{
buffer = 0; //ie recording is < approx 11 seconds long
}
double min = double.MaxValue;
double max = -double.MaxValue;
for (int i = buffer; i < arrayLength - buffer; i++)
{
if (dBarray[i] < min)
{
min = dBarray[i];
}
else if (dBarray[i] > max)
{
max = dBarray[i];
}
}
if (min <= SNR.MinimumDbBoundForEnvironmentalNoise)
{
min = SNR.MinimumDbBoundForEnvironmentalNoise;
}
// return the outs!
minDb = min;
maxDb = max;
var histo = new int[binCount];
var absThreshold = minDb + noiseThreshold_DB;
for (var i = 0; i < arrayLength; i++)
{
if (dBarray[i] <= absThreshold)
{
var id = (int)((dBarray[i] - minDb) / histogramBinWidth);
if (id >= binCount)
{
id = binCount - 1;
}
else if (id < 0)
{
id = 0;
}
histo[id]++;
}
}
var smoothHisto = DataTools.filterMovingAverage(histo, 3);
//DataTools.writeBarGraph(histo);
// find peak of lowBins histogram
SNR.GetModeAndOneStandardDeviation(smoothHisto, out var indexOfMode, out var indexOfOneSd);
// return remaining outs!
modeNoise = min + ((indexOfMode + 1) * histogramBinWidth); // modal noise level
sdNoise = (indexOfMode - indexOfOneSd) * histogramBinWidth; // SD of the noise
}