#define PI 3.141592654 /* mathematical constant */
#define T 0.1 /* threshold for local minima candidate */
#define F0_MAX 500
+#define CNLP 0.5 /* post processor constant */
/*---------------------------------------------------------------------------*\
};
float test_candidate_mbe(COMP Sw[], float f0);
+float post_process_mbe(COMP Fw[], int pmin, int pmax, float gmax);
+float post_process_sub_multiples(COMP Fw[],
+ int pmin, int pmax, float gmax, int gmax_bin);
extern int frames;
/*---------------------------------------------------------------------------*\
- void nlp()
-
- Determines the pitch in samples using the NLP algorithm. Returns the
- fundamental in Hz. Note that the actual pitch estimate is for the
- centre of the M sample Sn[] vector, not the current N sample input
- vector. This is (I think) a delay of 2.5 frames with N=80 samples.
- You should align further analysis using this pitch estimate to be
- centred on the middle of Sn[].
+ nlp()
+ Determines the pitch in samples using the Non Linear Pitch (NLP)
+ algorithm [1]. Returns the fundamental in Hz. Note that the actual
+ pitch estimate is for the centre of the M sample Sn[] vector, not
+ the current N sample input vector. This is (I think) a delay of 2.5
+ frames with N=80 samples. You should align further analysis using
+ this pitch estimate to be centred on the middle of Sn[].
+
+ Two post processors have been tried, the MBE version (as discussed
+ in [1]), and a post processor that checks sub-multiples. Both
+ suffer occasional gross pitch errors (i.e. neither are perfect). In
+ the presence of background noise the sub-multiple algorithm tends
+ towards low F0 which leads to better sounding background noise than
+ the MBE post processor.
+
+ A good way to test and develop the NLP pitch estimator is using the
+ tnlp (codec2/unittest) and the codec2/octave/plnlp.m Octave script.
+
+ A pitch tracker searching a few frames forward and backward in time
+ would be a useful addition.
+
+ References:
+
+ [1] http://www.itr.unisa.edu.au/~steven/thesis/dgr.pdf Chapter 4
+
\*---------------------------------------------------------------------------*/
float nlp(
static float mem_fir[NLP_NTAP];/* decimation FIR filter memory */
COMP Fw[PE_FFT_SIZE]; /* DFT of squared signal */
float gmax;
-
- float candidate_f0;
- float f0,best_f0; /* fundamental frequency */
- float e,e_min; /* MBE cost function */
- int i,j;
- float e_hz[F0_MAX];
- int bin;
+ int gmax_bin;
+ int i,j;
+ float best_f0;
/* Square, notch filter at DC, and LP filter vector */
for(i=PE_FFT_SIZE*DEC/pmax; i<=PE_FFT_SIZE*DEC/pmin; i++) {
if (Fw[i].real > gmax) {
gmax = Fw[i].real;
+ gmax_bin = i;
}
}
+ #ifdef POST_PROCESS_MBE
+ best_f0 = post_process_mbe(Fw, pmin, pmax, gmax);
+ #else
+ best_f0 = post_process_sub_multiples(Fw, pmin, pmax, gmax, gmax_bin);
+ #endif
+
+ /* Shift samples in buffer to make room for new samples */
+
+ for(i=0; i<m-n+d; i++)
+ sq[i] = sq[i+n];
+
+ /* return pitch and F0 estimate */
+
+ *pitch = (float)SAMPLE_RATE/best_f0;
+ return(best_f0);
+}
+
+/*---------------------------------------------------------------------------*\
+
+ post_process_sub_multiples()
+
+ Given the global maximma of Fw[] we search interger submultiples for
+ local maxima. If local maxima exist and they are above an
+ experimentally derived threshold (OK a magic number I pulled out of
+ the air) we choose the submultiple as the F0 estimate.
+
+ The rational for this is that the lowest frequency peak of Fw[]
+ should be F0, as Fw[] can be considered the autocorrelation function
+ of Sw[] (the speech spectrum). However sometimes due to phase
+ effects the lowest frequency maxima may not be the global maxima.
+
+ This works OK in practice and favours low F0 values in the presence
+ of background noise which means the sinusoidal codec does an OK job
+ of synthesising the background noise. High F0 in background noise
+ tends to sound more periodic introducing annoying artifacts.
+
+\*---------------------------------------------------------------------------*/
+
+float post_process_sub_multiples(COMP Fw[],
+ int pmin, int pmax, float gmax, int gmax_bin)
+{
+ int min_bin, cmax_bin;
+ int mult;
+ float thresh, best_f0;
+ int b, bmin, bmax, lmax_bin;
+ float lmax, cmax;
+
+ /* post process estimate by searching submultiples */
+
+ mult = 2;
+ min_bin = PE_FFT_SIZE*DEC/pmax;
+ thresh = CNLP*gmax;
+ cmax_bin = gmax_bin;
+
+ while(gmax_bin/mult >= min_bin) {
+
+ b = gmax_bin/mult; /* determine search interval */
+ bmin = 0.8*b;
+ bmax = 1.2*b;
+ if (bmin < min_bin)
+ bmin = min_bin;
+
+ lmax = 0;
+ for (b=bmin; b<=bmax; b++) /* look for maximum in interval */
+ if (Fw[b].real > lmax) {
+ lmax = Fw[b].real;
+ lmax_bin = b;
+ }
+
+ if (lmax > thresh)
+ if (lmax > Fw[lmax_bin-1].real && lmax > Fw[lmax_bin+1].real) {
+ cmax = lmax;
+ cmax_bin = lmax_bin;
+ }
+
+ mult++;
+ }
+
+ best_f0 = (float)cmax_bin*SAMPLE_RATE/(PE_FFT_SIZE*DEC);
+
+ return best_f0;
+}
+
+/*---------------------------------------------------------------------------*\
+
+ post_process_mbe()
+
+ Use the MBE pitch estimation algorithm to evaluate pitch candidates. This
+ works OK but the accuracy at low F0 is affected by NW, the analysis window
+ size used for the DFT of the input speech Sw[]. Also favours high F0 in
+ the presence of background noise which causes periodic artifacts in the
+ synthesised speech.
+
+\*---------------------------------------------------------------------------*/
+
+float post_process_mbe(COMP Fw[], int pmin, int pmax, float gmax)
+{
+ float candidate_f0;
+ float f0,best_f0; /* fundamental frequency */
+ float e,e_min; /* MBE cost function */
+ int i;
+ float e_hz[F0_MAX];
+ int bin;
+ float f0_min, f0_max;
+ float f0_start, f0_end;
+
+ f0_min = (float)SAMPLE_RATE/pmax;
+ f0_max = (float)SAMPLE_RATE/pmin;
+
/* Now look for local maxima. Each local maxima is a candidate
that we test using the MBE pitch estimation algotithm */
/* OK, sample MBE cost function over +/- 10Hz range in 2.5Hz steps */
candidate_f0 = (float)i*SAMPLE_RATE/(PE_FFT_SIZE*DEC);
- if (frames == 29)
- printf("candidate F0: %f\n", candidate_f0);
- for(f0=candidate_f0-20; f0<=candidate_f0+20; f0+= 2.5) {
+ f0_start = candidate_f0-20;
+ f0_end = candidate_f0+20;
+ if (f0_start < f0_min) f0_start = f0_min;
+ if (f0_end > f0_max) f0_end = f0_max;
+
+ for(f0=f0_start; f0<=f0_end; f0+= 2.5) {
e = test_candidate_mbe(Sw, f0);
bin = floor(f0); assert((bin > 0) && (bin < F0_MAX));
e_hz[bin] = e;
- if (frames == 29)
- printf("f0: %f e: %f e_min: %f best_f0: %f\n",
- f0, e, e_min, best_f0);
if (e < e_min) {
e_min = e;
best_f0 = f0;
}
dump_e(e_hz);
- /* Shift samples in buffer to make room for new samples */
-
- for(i=0; i<m-n+d; i++)
- sq[i] = sq[i+n];
-
- /* return pitch and F0 estimate */
-
- *pitch = (float)SAMPLE_RATE/best_f0;
- return(best_f0);
+ return best_f0;
}
-
+
/*---------------------------------------------------------------------------*\
test_candidate_mbe()
float den; /* denominator of Am expression */
float error; /* accumulated error between originl and synthesised */
float Wo; /* current "test" fundamental freq. */
- int L; /* number of bands */
-
+ int L;
+
+ L = floor((SAMPLE_RATE/2.0)/f0);
Wo = f0*(2*PI/SAMPLE_RATE);
- L = floor(PI/Wo);;
error = 0.0;
projects / freetel-svn-tracking.git / commitdiff