void setup() {
stream.setLabelsForAllDimensions({"audio"});
pipeline.addFeatureExtractionModule(
FFT(kFftWindowSize, kFftHopSize,
DIM, FFT::HAMMING_WINDOW, true, false));
MFCC::Options options;
options.sample_rate = kSampleRate;
options.fft_size = kFftWindowSize / 2;
options.start_freq = 300;
options.end_freq = 3700;
options.num_tri_filter = 26;
options.num_cepstral_coeff = 12;
options.lifter_param = 22;
options.use_vad = true;
options.noise_level = noise_level;
pipeline.addFeatureExtractionModule(MFCC(options));
pipeline.setClassifier(SVM());
// GMM(16, true, false, 1, 100, 0.001));
// In post processing, we wait #n predicitons. If m out of n predictions are
// from the same class, we declare the class as the right one.
//
// n = (duration * sample_rate) / frame_size
// where duration = post_duration
// sample_rate = kSampleRate
// frame_size = kFftHopSize
// m = n * post_ratio
int num_predictions = post_duration / 1000 * kSampleRate / kFftHopSize;
pipeline.addPostProcessingModule(
ClassLabelFilter(num_predictions * post_ratio, num_predictions));
auto ratio_updater = [](double new_ratio) {
ClassLabelFilter* filter =
dynamic_cast<ClassLabelFilter*>(pipeline.getPostProcessingModule(0));
// Recalculate num_predictions as post_duration might have been changed
int num_predictions = post_duration / 1000 * kSampleRate / kFftHopSize;
filter->setMinimumCount(new_ratio * num_predictions);
};
auto duration_updater = [](int new_duration) {
ClassLabelFilter* filter =
dynamic_cast<ClassLabelFilter*>(pipeline.getPostProcessingModule(0));
// Recalculate num_predictions as post_duration might have been changed
int num_predictions = post_duration / 1000 * kSampleRate / kFftHopSize;
filter->setBufferSize(num_predictions);
};
auto noise_updater = [](int new_noise_level) {
MFCC *mfcc = dynamic_cast<MFCC*>(pipeline.getFeatureExtractionModule(1));
mfcc->setNoiseLevel(new_noise_level);
};
registerTuneable(noise_level, 0, 20,
"Noise Level",
"The threshold for the system to distinguish between "
"ambient noise and speech/sound",
noise_updater);
registerTuneable(post_duration, 0, 2000,
"Duration",
"Time (in ms) that is considered as a whole "
"for smoothing the prediction",
duration_updater);
registerTuneable(post_ratio, 0.0f, 1.0f,
"Ratio",
"The portion of time in duration that "
"should be from the same class",
ratio_updater);
useInputStream(stream);
useOutputStream(oStream);
usePipeline(pipeline);
useLeaveOneOutScoring(false);
setGUIBufferSize(kSampleRate);
}
int main (int argc, char **argv)
{
float mfcc_result[NUMFILTERBANK-1];
FILE *fptr;
float Min=0.0f,Max=0.0f;
int16_t *samples = NULL;
uint16_t numFrame = 0;
uint16_t i,j,k;
int32_t Val_RGB;
uint32_t idxCoeff;
int tmp;
char Len;
Len = strlen(argv[1]);
for ( i=0; i < Len-4; i++)
{
FileOut[i]= argv[1][i];
FileOutTxt[i]= argv[1][i];
}
FileOut[Len-4] = '.';
FileOut[Len-3] = 'b';
FileOut[Len-2] = 'm';
FileOut[Len-1] = 'p';
FileOut[Len] = '\0';
FileOutTxt[Len-4] = '.';
FileOutTxt[Len-3] = 't';
FileOutTxt[Len-2] = 'x';
FileOutTxt[Len-1] = 't';
FileOutTxt[Len] = '\0';
/* Sotarage MFCC coeffience */
fptr=fopen(FileOutTxt,"w");
PreCalcFilterBank(FilterBank,fNorm, NUMBINHALF, NUMFILTERBANK);
//printf("Length: %d \n", strlen(argv[1]));
wavread(argv[1], &samples);
printf("No. of channels: %d\n", header->num_channels);
printf("Sample rate: %d\n", header->sample_rate);
printf("Bit rate: %dkbps\n", header->byte_rate*8 / 1000);
printf("Bits per sample: %d\n\n", header->bps);
//printf("Sample 0: %d\n", samples[0]);
//printf("Sample 1: %d\n", samples[1]);
// Modify the header values & samples before writing the new file
wavwrite("track2.wav", samples);
numFrame = header->datachunk_size/(2*2*NUMBINHALF) ;
//printf("Num Frame: %d \n", numFrame );
/*
BMP = (RGB_data **)malloc((NUMFILTERBANK-1)*sizeof(RGB_data*));
for (i=0; i < NUMFILTERBANK-1; i++)
{
BMP[i] = (RGB_data *)malloc(sizeof(RGB_data)*(2*numFrame)) ;
if(BMP[i] == NULL)
{
fprintf(stderr, "out of memory\n");
exit (0);
}
}
*/
BMP = (RGB_data *)malloc((NUMFILTERBANK-1)*sizeof(RGB_data*)*2*numFrame);
//memset(BMP, 0, sizeof(BMP));
for (i = 0; i < 2*numFrame-1; i++)
{
for (j=0; j< 2*NUMBINHALF;j++)
{
V[j].Re = (float)(samples[i*NUMBINHALF + j]);
//printf(" %d", samples[i*NUMBINHALF + j]);
V[j].Im = (float)0.0f;
}
//printf("\n");
MFCC(V, FilterBank ,fNorm, mfcc_result);
//printf("MFCC:");
for(idxCoeff = 0; idxCoeff < NUMFILTERBANK -1; idxCoeff++)
{
fprintf(fptr,"%f ", mfcc_result[idxCoeff]);
//Val_RGB = (int)(255/(63.164356+46.877232)*(mfcc_result[idxCoeff]+10));
Val_RGB = (int)(255*(mfcc_result[idxCoeff]));
//Val_RGB = tmp*tmp;
//Val_RGB = Val_RGB/255;
if (Val_RGB < 0) Val_RGB = 0;
if (Val_RGB > 255) Val_RGB = 255;
BMP[(NUMFILTERBANK - idxCoeff-2)*2*numFrame +i].g = (BYTE)(Val_RGB);
BMP[(NUMFILTERBANK - idxCoeff-2)*2*numFrame +i].b = (BYTE)(Val_RGB);
BMP[(NUMFILTERBANK - idxCoeff-2)*2*numFrame +i].r = (BYTE)(Val_RGB);
//BMP[NUMFILTERBANK - idxCoeff-1][i].b = (BYTE)((Val_RGB & 0x00FF00)>>8);
//BMP[NUMFILTERBANK - idxCoeff-1][i].r = (BYTE)((Val_RGB & 0xFF0000)>>16);
//printf(" %d ", Val_RGB);
//if (mfcc_result[idxCoeff] < Min) Min=mfcc_result[idxCoeff];
//if (mfcc_result[idxCoeff] > Max) Max=mfcc_result[idxCoeff];
}
fprintf(fptr,"\r\n");
}
//printf("Min: %f Max: %f \n", Min, Max);
bmp_generator(FileOut, 2*numFrame, NUMFILTERBANK -1 ,(BYTE*) (BMP));
//bmpread("record_21.bmp");
free(header);
free(samples);
free(BMP);
fclose(fptr);
exit (0);
}
