public (List <double[]> composed_mfcc, List <double[]> composed_delta, List <double[]> composed_delta_delta) ExtractCoefficientFromAudio(string filePath)
{
var audio = _audioService.GetSignal(filePath);
var mfcc = new MelFrequencyCepstrumCoefficient(
filterCount: 26,
cepstrumCount: 13,
lowerFrequency: 300,
upperFrequency: audio.SampleRate / 2,
alpha: 0.97,
samplingRate:
audio.SampleRate,
frameRate: 25,
windowLength: 0.0257,
numberOfBins: 512);
var cepstrumCoefficients = mfcc.Transform(audio).Select(_ => _.Descriptor).ToList();
double[,] mfcc_list = cepstrumCoefficients.CreateRectangularArray();
var delta = mfcc_list.performDelta2D();
var deltaDelta = delta.performDelta2D();
List <double[]> composed_mfcc = mfcc_list.ToJaggedArray().ToList();
List <double[]> composed_delta = delta.ToJaggedArray().ToList();
List <double[]> composed_delta_delta = deltaDelta.ToJaggedArray().ToList();
return(composed_mfcc : composed_mfcc, composed_delta : composed_delta, composed_delta_delta : composed_delta_delta);
}
public void sample_test()
{
string basePath = NUnit.Framework.TestContext.CurrentContext.TestDirectory;
FreeSpokenDigitsDataset fsdd = new FreeSpokenDigitsDataset(Path.Combine(basePath, "mfcc"));
var mfcc = new MelFrequencyCepstrumCoefficient();
Signal a = fsdd.GetSignal(0, "jackson", 10);
MelFrequencyCepstrumCoefficientDescriptor[] ra = mfcc.Transform(a).ToArray();
Assert.AreEqual(35, ra.Length);
Assert.IsTrue(new double[] { 10.570020645259348d, 1.3484344242338475d, 0.4861056552885234d, -0.79287993818868352d, -0.64182784362935996d, -0.28079835895392041d, -0.46378109632237779d, 0.072039410871952647d, -0.43971730320461733d, 0.48891921252102533d, -0.22502241185050212d, 0.12478713268421229d, -0.13373400147110801d }.IsEqual(ra[0].Descriptor, 1e-8));
Signal b = fsdd.GetSignal(0, "nicolas", 10);
MelFrequencyCepstrumCoefficientDescriptor[] rb = mfcc.Transform(b).ToArray();
Assert.AreEqual(24, rb.Length);
Assert.IsTrue(new[] { 10.6434445230168, -0.222107787197107, 0.316067614396639, -0.212769536249701, -0.107755264262885, -0.292732772820073, -0.00445205345925395, 0.024397440969199, 0.0213769364471326, -0.0882765552657509, -0.177682484734242, -0.1013307739251, -0.099014915302743 }.IsEqual(rb[0].Descriptor, 1e-8));
Signal c = fsdd.GetSignal(5, "theo", 23);
MelFrequencyCepstrumCoefficientDescriptor[] rc = mfcc.Transform(c).ToArray();
Assert.AreEqual(27, rc.Length);
Assert.IsTrue(new[] { 7.24614406589037, -1.16796769512142, -0.134374026111248, -0.192703972718674, 0.112752647291759, -0.118712048308068, -0.0603752892245708, -0.0275002195634854, -0.0830858413953528, -0.0838965948140795, -0.15293502718595, 0.0107796827068413, -0.0491283773795346 }.IsEqual(rc[0].Descriptor, 1e-8));
}
public static double[] GetMfcc(string file)
{
WaveDecoder decoder = new WaveDecoder(file);
Signal signal = decoder.Decode();
MelFrequencyCepstrumCoefficient mfcc = new MelFrequencyCepstrumCoefficient();
MelFrequencyCepstrumCoefficientDescriptor[] ra = mfcc.Transform(signal).ToArray();
var query = from x in ra select x.Descriptor.Average();
return(query.ToArray());
}
public static IEnumerable <MelFrequencyCepstrumCoefficientDescriptor> ObterMFCCDescriptor(Signal signal)
{
using (var mfcc = new MelFrequencyCepstrumCoefficient(filterCount: 20, samplingRate: signal.SampleRate))
{
var mfccTransformResult = mfcc.Transform(signal);
foreach (var mfccTransformItem in mfccTransformResult)
{
yield return(mfccTransformItem);
}
}
}
public IEnumerable <MelFrequencyCepstrumCoefficientDescriptor> ObterAudioFiltrado()
{
using (var signal = ObterSinal())
using (var mfcc = new MelFrequencyCepstrumCoefficient())
{
var mfccTransformResult = mfcc.Transform(signal);
//signal.RawData
foreach (var mfccTransformItem in mfccTransformResult)
{
yield return(mfccTransformItem);
}
}
}
// get record from file
public Record(String path, String label)
{
WaveChannel32 wave = new WaveChannel32(new WaveFileReader(path));
this.path = path;
this.label = label;
this.frames = new List <RecordFrame>();
byte[] buffer = new byte[16384];
int read = 0;
List <double> listSamples = new List <double>();
int sampleRate = 16000;
while (wave.Position < wave.Length)
{
read = wave.Read(buffer, 0, 16384);
for (int i = 0; i < read / 4; i++)
{
double sample = BitConverter.ToSingle(buffer, i * 4);
listSamples.Add(sample);
}
}
Signal signal = Signal.FromArray(listSamples.ToArray(), sampleRate);
MelFrequencyCepstrumCoefficient mfcc = new MelFrequencyCepstrumCoefficient();
IEnumerable <MelFrequencyCepstrumCoefficientDescriptor> features = mfcc.Transform(signal);
foreach (var t in features)
{
RecordFrame recordFrame = new RecordFrame();
recordFrame.coefficients = new List <double>(t.Descriptor);
recordFrame.label = label;
this.frames.Add(recordFrame);
}
}
public void sample_test()
{
string basePath = NUnit.Framework.TestContext.CurrentContext.TestDirectory;
string pathWhereTheDatasetShouldBeStored = Path.Combine(basePath, "mfcc");
#region doc_example1
// Let's say we would like to analyse an audio sample. To give an example that
// could be reproduced by anyone without having to give a specific sound file
// that would need to have been downloaded by every user trying to run this example,
// we will use obtain an example from the Free Spoken Digits Dataset instead:
var fsdd = new FreeSpokenDigitsDataset(path: pathWhereTheDatasetShouldBeStored);
// Let's obtain one of the audio signals:
Signal a = fsdd.GetSignal(0, "jackson", 10);
// Note: if you would like to load a signal from the
// disk, you could use the following method directly:
// Signal a = Signal.FromFile(fileName);
// First we could extract some characteristics from the audio signal, just
// for informative purposes. We don't actually need to register them just
// to compute the MFCC, so please skip those checks if you would like!
int numberOfChannels = a.NumberOfChannels; // should be: 1
int numberOfFrames = a.NumberOfFrames; // should be: 5451
int numberOfSamples = a.NumberOfSamples; // should be: 5451
SampleFormat format = a.SampleFormat; // should be: Format32BitIeeeFloat
int sampleRate = a.SampleRate; // should be: 8000 (8khz)
int samples = a.Samples; // should be: 5451
int sampleSize = a.SampleSize; // should be: 4
int numberOfBytes = a.NumberOfBytes; // should be: 21804
// Now, let's say we would like to compute its MFCC:
var extractor = new MelFrequencyCepstrumCoefficient(
filterCount: 40, // Note: all values are optional, you can
cepstrumCount: 13, // specify only the ones you'd like and leave
lowerFrequency: 133.3333, // all others at their defaults
upperFrequency: 6855.4976,
alpha: 0.97,
samplingRate: 16000,
frameRate: 100,
windowLength: 0.0256,
numberOfBins: 512);
// We can call the transform method of the MFCC extractor class:
IEnumerable <MelFrequencyCepstrumCoefficientDescriptor> mfcc = extractor.Transform(a);
// or we could also transform them to a matrix directly with:
double[][] actual = mfcc.Select(x => x.Descriptor).ToArray();
// This matrix would contain X different MFCC values (due the length of the signal)
int numberOfMFCCs = actual.Length; // should be 35 (depends on the MFCC window)
// Each of those MFCC values would have length 13;
int descriptorLength = actual[0].Length; // 13 (depends on the MFCC Ceptrtum's count)
// An example of an MFCC vector would have been:
double[] row = actual[0]; // should have been: (see vector written below)
double[] expected = new double[]
{
10.570020645259348d, 1.3484344242338475d, 0.4861056552885234d,
-0.79287993818868352d, -0.64182784362935996d, -0.28079835895392041d,
-0.46378109632237779d, 0.072039410871952647d, -0.43971730320461733d,
0.48891921252102533d, -0.22502241185050212d, 0.12478713268421229d, -0.13373400147110801d
};
#endregion
Assert.AreEqual(1, numberOfChannels);
Assert.AreEqual(5451, numberOfFrames);
Assert.AreEqual(5451, numberOfSamples);
Assert.AreEqual(SampleFormat.Format32BitIeeeFloat, format);
Assert.AreEqual(8000, sampleRate);
Assert.AreEqual(5451, samples);
Assert.AreEqual(4, sampleSize);
Assert.AreEqual(21804, numberOfBytes);
Assert.AreEqual(sampleSize * numberOfFrames * numberOfChannels, numberOfBytes);
Assert.AreEqual(35, numberOfMFCCs);
Assert.IsTrue(expected.IsEqual(row, 1e-8));
Signal b = fsdd.GetSignal(0, "nicolas", 10);
Assert.AreEqual(2, b.NumberOfChannels);
Assert.AreEqual(3755, b.NumberOfFrames);
Assert.AreEqual(7510, b.NumberOfSamples);
Assert.AreEqual(SampleFormat.Format32BitIeeeFloat, b.SampleFormat);
Assert.AreEqual(8000, b.SampleRate);
Assert.AreEqual(7510, b.Samples);
Assert.AreEqual(4, b.SampleSize);
Assert.AreEqual(30040, b.NumberOfBytes);
Assert.AreEqual(b.SampleSize * b.NumberOfFrames * b.NumberOfChannels, b.NumberOfBytes);
MelFrequencyCepstrumCoefficientDescriptor[] rb = extractor.Transform(b).ToArray();
Assert.AreEqual(24, rb.Length);
Assert.IsTrue(new[] { 10.6434445230168, -0.222107787197107, 0.316067614396639, -0.212769536249701, -0.107755264262885, -0.292732772820073, -0.00445205345925395, 0.024397440969199, 0.0213769364471326, -0.0882765552657509, -0.177682484734242, -0.1013307739251, -0.099014915302743 }.IsEqual(rb[0].Descriptor, 1e-8));
Signal c = fsdd.GetSignal(5, "theo", 23);
Assert.AreEqual(1, c.NumberOfChannels);
Assert.AreEqual(4277, c.NumberOfFrames);
Assert.AreEqual(4277, c.NumberOfSamples);
Assert.AreEqual(SampleFormat.Format32BitIeeeFloat, c.SampleFormat);
Assert.AreEqual(8000, c.SampleRate);
Assert.AreEqual(4277, c.Samples);
Assert.AreEqual(4, c.SampleSize);
Assert.AreEqual(17108, c.NumberOfBytes);
Assert.AreEqual(b.SampleSize * c.NumberOfFrames * c.NumberOfChannels, c.NumberOfBytes);
MelFrequencyCepstrumCoefficientDescriptor[] rc = extractor.Transform(c).ToArray();
Assert.AreEqual(27, rc.Length);
Assert.IsTrue(new[] { 7.24614406589037, -1.16796769512142, -0.134374026111248, -0.192703972718674, 0.112752647291759, -0.118712048308068, -0.0603752892245708, -0.0275002195634854, -0.0830858413953528, -0.0838965948140795, -0.15293502718595, 0.0107796827068413, -0.0491283773795346 }.IsEqual(rc[0].Descriptor, 1e-8));
}
