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Diffstat (limited to 'gr-vocoder/lib/codec2/nlp.c')
| -rw-r--r-- | gr-vocoder/lib/codec2/nlp.c | 364 |
1 files changed, 0 insertions, 364 deletions
diff --git a/gr-vocoder/lib/codec2/nlp.c b/gr-vocoder/lib/codec2/nlp.c deleted file mode 100644 index 0d5e530ce..000000000 --- a/gr-vocoder/lib/codec2/nlp.c +++ /dev/null @@ -1,364 +0,0 @@ -/*---------------------------------------------------------------------------*\ - - FILE........: nlp.c - AUTHOR......: David Rowe - DATE CREATED: 23/3/93 - - Non Linear Pitch (NLP) estimation functions. - -\*---------------------------------------------------------------------------*/ - -/* - Copyright (C) 2009 David Rowe - - All rights reserved. - - This program is free software; you can redistribute it and/or modify - it under the terms of the GNU Lesser General Public License version 2.1, as - published by the Free Software Foundation. This program is - distributed in the hope that it will be useful, but WITHOUT ANY - WARRANTY; without even the implied warranty of MERCHANTABILITY or - FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public - License for more details. - - You should have received a copy of the GNU Lesser General Public License - along with this program; if not, see <http://www.gnu.org/licenses/>. -*/ - -#include "defines.h" -#include "nlp.h" -#include "dump.h" -#include "fft.h" - -#include <assert.h> -#include <math.h> -#include <stdlib.h> - -/*---------------------------------------------------------------------------*\ - - DEFINES - -\*---------------------------------------------------------------------------*/ - -#define PMAX_M 600 /* maximum NLP analysis window size */ -#define COEFF 0.95 /* notch filter parameter */ -#define PE_FFT_SIZE 512 /* DFT size for pitch estimation */ -#define DEC 5 /* decimation factor */ -#define SAMPLE_RATE 8000 -#define PI 3.141592654 /* mathematical constant */ -#define T 0.1 /* threshold for local minima candidate */ -#define F0_MAX 500 -#define CNLP 0.3 /* post processor constant */ -#define NLP_NTAP 48 /* Decimation LPF order */ - -/*---------------------------------------------------------------------------*\ - - GLOBALS - -\*---------------------------------------------------------------------------*/ - -/* 48 tap 600Hz low pass FIR filter coefficients */ - -const float nlp_fir[] = { - -1.0818124e-03, - -1.1008344e-03, - -9.2768838e-04, - -4.2289438e-04, - 5.5034190e-04, - 2.0029849e-03, - 3.7058509e-03, - 5.1449415e-03, - 5.5924666e-03, - 4.3036754e-03, - 8.0284511e-04, - -4.8204610e-03, - -1.1705810e-02, - -1.8199275e-02, - -2.2065282e-02, - -2.0920610e-02, - -1.2808831e-02, - 3.2204775e-03, - 2.6683811e-02, - 5.5520624e-02, - 8.6305944e-02, - 1.1480192e-01, - 1.3674206e-01, - 1.4867556e-01, - 1.4867556e-01, - 1.3674206e-01, - 1.1480192e-01, - 8.6305944e-02, - 5.5520624e-02, - 2.6683811e-02, - 3.2204775e-03, - -1.2808831e-02, - -2.0920610e-02, - -2.2065282e-02, - -1.8199275e-02, - -1.1705810e-02, - -4.8204610e-03, - 8.0284511e-04, - 4.3036754e-03, - 5.5924666e-03, - 5.1449415e-03, - 3.7058509e-03, - 2.0029849e-03, - 5.5034190e-04, - -4.2289438e-04, - -9.2768838e-04, - -1.1008344e-03, - -1.0818124e-03 -}; - -typedef struct { - float sq[PMAX_M]; /* squared speech samples */ - float mem_x,mem_y; /* memory for notch filter */ - float mem_fir[NLP_NTAP]; /* decimation FIR filter memory */ -} NLP; - -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, - float *prev_Wo); - -/*---------------------------------------------------------------------------*\ - - nlp_create() - - Initialisation function for NLP pitch estimator. - -\*---------------------------------------------------------------------------*/ - -void *nlp_create() -{ - NLP *nlp; - int i; - - nlp = (NLP*)malloc(sizeof(NLP)); - if (nlp == NULL) - return NULL; - - for(i=0; i<PMAX_M; i++) - nlp->sq[i] = 0.0; - nlp->mem_x = 0.0; - nlp->mem_y = 0.0; - for(i=0; i<NLP_NTAP; i++) - nlp->mem_fir[i] = 0.0; - - return (void*)nlp; -} - -/*---------------------------------------------------------------------------*\ - - nlp_destory() - - Initialisation function for NLP pitch estimator. - -\*---------------------------------------------------------------------------*/ - -void nlp_destroy(void *nlp_state) -{ - assert(nlp_state != NULL); - free(nlp_state); -} - -/*---------------------------------------------------------------------------*\ - - 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( - void *nlp_state, - float Sn[], /* input speech vector */ - int n, /* frames shift (no. new samples in Sn[]) */ - int m, /* analysis window size */ - int pmin, /* minimum pitch value */ - int pmax, /* maximum pitch value */ - float *pitch, /* estimated pitch period in samples */ - COMP Sw[], /* Freq domain version of Sn[] */ - float *prev_Wo -) -{ - NLP *nlp; - float notch; /* current notch filter output */ - COMP Fw[PE_FFT_SIZE]; /* DFT of squared signal */ - float gmax; - int gmax_bin; - int i,j; - float best_f0; - - assert(nlp_state != NULL); - nlp = (NLP*)nlp_state; - - /* Square, notch filter at DC, and LP filter vector */ - - for(i=m-n; i<M; i++) /* square latest speech samples */ - nlp->sq[i] = Sn[i]*Sn[i]; - - for(i=m-n; i<m; i++) { /* notch filter at DC */ - notch = nlp->sq[i] - nlp->mem_x; - notch += COEFF*nlp->mem_y; - nlp->mem_x = nlp->sq[i]; - nlp->mem_y = notch; - nlp->sq[i] = notch; - } - - for(i=m-n; i<m; i++) { /* FIR filter vector */ - - for(j=0; j<NLP_NTAP-1; j++) - nlp->mem_fir[j] = nlp->mem_fir[j+1]; - nlp->mem_fir[NLP_NTAP-1] = nlp->sq[i]; - - nlp->sq[i] = 0.0; - for(j=0; j<NLP_NTAP; j++) - nlp->sq[i] += nlp->mem_fir[j]*nlp_fir[j]; - } - - /* Decimate and DFT */ - - for(i=0; i<PE_FFT_SIZE; i++) { - Fw[i].real = 0.0; - Fw[i].imag = 0.0; - } - for(i=0; i<m/DEC; i++) { - Fw[i].real = nlp->sq[i*DEC]*(0.5 - 0.5*cos(2*PI*i/(m/DEC-1))); - } -#ifdef DUMP - dump_dec(Fw); -#endif - fft(&Fw[0].real,PE_FFT_SIZE,1); - for(i=0; i<PE_FFT_SIZE; i++) - Fw[i].real = Fw[i].real*Fw[i].real + Fw[i].imag*Fw[i].imag; - -#ifdef DUMP - dump_sq(nlp->sq); - dump_Fw(Fw); -#endif - - /* find global peak */ - - gmax = 0.0; - gmax_bin = PE_FFT_SIZE*DEC/pmax; - 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; - } - } - - best_f0 = post_process_sub_multiples(Fw, pmin, pmax, gmax, gmax_bin, - prev_Wo); - - /* Shift samples in buffer to make room for new samples */ - - for(i=0; i<m-n; i++) - nlp->sq[i] = nlp->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, - float *prev_Wo) -{ - int min_bin, cmax_bin; - int mult; - float thresh, best_f0; - int b, bmin, bmax, lmax_bin; - float lmax, cmax; - int prev_f0_bin; - - /* post process estimate by searching submultiples */ - - mult = 2; - min_bin = PE_FFT_SIZE*DEC/pmax; - cmax_bin = gmax_bin; - prev_f0_bin = *prev_Wo*(4000.0/PI)*(PE_FFT_SIZE*DEC)/SAMPLE_RATE; - - 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; - - /* lower threshold to favour previous frames pitch estimate, - this is a form of pitch tracking */ - - if ((prev_f0_bin > bmin) && (prev_f0_bin < bmax)) - thresh = CNLP*0.5*gmax; - else - thresh = CNLP*gmax; - - lmax = 0; - lmax_bin = bmin; - 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; -} - |