static float RecognizeAudio(string path, string svmModel)
{
SVMAudio mySVM = new SVMAudio();
mySVM.LoadSVMFromFile(svmModel);
double[] y = AudioFeatures.load2(path);
double[,] mfcc_mass = MFCC_calculating.MFCC_20_calculation(y);
double[] features_vector = FeaturesFromMFCC(mfcc_mass);
int features_size = 100;
Image <Gray, float> features = new Image <Gray, float>(features_size, 1);
Image <Gray, float> results = new Image <Gray, float>(1, 1);
AudioFeatures.NormalizeFromFile(@"C:\Projeto\autoleitura\paulorenato\AudioCSharp\Modelo\scaleSVMTrain.txt", features_vector);
for (int i = 0; i < features_size; i++)
{
features.Data[0, i, 0] = (float)features_vector[i];
}
mySVM.Predict(features, results);
return(results.Data[0, 0, 0]);
}
public static double[][] getDataFromBase(String path, string fileName)
{
DirectoryInfo dir = new DirectoryInfo(path);
DirectoryInfo[] subDirs = dir.GetDirectories();
double[][] data = new double[4125][];
int audioIndex = 0;
//Salvar Características
string file_full_path = Path.Combine(@"C:\Projeto\autoleitura\paulorenato\AudioCSharp\Caracteristicas", fileName);
StreamWriter fileStream = new StreamWriter(file_full_path);
foreach (DirectoryInfo sub in subDirs)
{
FileInfo[] files = sub.GetFiles("*.wav");
Console.WriteLine("Current working directory: " + sub.Name);
foreach (FileInfo file in files)
{
data[audioIndex] = new double[101];
int featureIndex = 0;
double[] y = load2(file.FullName);
double[,] mfcc_mass = MFCC_calculating.MFCC_20_calculation(y);
int count_frames = mfcc_mass.Length / 20;
for (int i = 0; i < 20; i++)
{
double media = 0.0;
double max = Double.MinValue;
double min = Double.MaxValue;
double[] values = new double[count_frames];
for (int k = 0; k < count_frames; k++)
{
if (mfcc_mass[k, i] < min)
{
min = mfcc_mass[k, i];
}
if (mfcc_mass[k, i] > max)
{
max = mfcc_mass[k, i];
}
media += mfcc_mass[k, i];
values[k] = mfcc_mass[k, i];
}
media = media / count_frames;
double variance = Variance(values, media);
double mediana = GetMedian(values);
data[audioIndex][featureIndex++] = mediana;
data[audioIndex][featureIndex++] = media;
data[audioIndex][featureIndex++] = variance;
data[audioIndex][featureIndex++] = min;
data[audioIndex][featureIndex++] = max;
fileStream.Write(mediana.ToString("0.000000000", System.Globalization.CultureInfo.InvariantCulture) + ",");
fileStream.Write(media.ToString("0.000000000", System.Globalization.CultureInfo.InvariantCulture) + ",");
fileStream.Write(variance.ToString("0.00000000000", System.Globalization.CultureInfo.InvariantCulture) + ",");
fileStream.Write(min.ToString("0.000000000", System.Globalization.CultureInfo.InvariantCulture) + ",");
fileStream.Write(max.ToString("0.000000000", System.Globalization.CultureInfo.InvariantCulture) + ",");
}
data[audioIndex][featureIndex] = (double)int.Parse(sub.Name);
fileStream.WriteLine(int.Parse(sub.Name));
fileStream.Flush();
audioIndex++;
}
}
fileStream.Flush();
return(data);
}