FreeCalypso > hg > efr-experiments
view src/vad.c @ 6:6119d2c1e7d9
EFR2 encoder: mimic 5 ms delay of AMR
author | Mychaela Falconia <falcon@freecalypso.org> |
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date | Wed, 03 Apr 2024 07:14:01 +0000 |
parents | 56410792419a |
children |
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/*************************************************************************** * * File Name: vad.c * * Purpose: Contains all functions for voice activity detection, as * described in the high level specification of VAD. * * Below is a listing of all the functions appearing in the file. * The functions are arranged according to their purpose. Under * each heading, the ordering is hierarchical. * * Resetting of static variables of VAD: * reset_vad() * * Main routine of VAD (called by the speech encoder): * vad_computation() * Adaptive filtering and energy computation: * energy_computation() * Averaging of autocorrelation function values: * acf_averaging() * Computation of predictor values: * predictor_values() * schur_recursion() * step_up() * compute_rav1() * Spectral comparison: * spectral_comparison() * Information tone detection: * tone_detection() * step_up() * Threshold adaptation: * threshold_adaptation() * VAD decision: * vad_decision() * VAD hangover addition: * vad_hangover() * * Periodicity detection routine (called by the speech encoder): * periodicity_detection() * **************************************************************************/ #include "typedef.h" #include "cnst.h" #include "basic_op.h" #include "oper_32b.h" #include "count.h" #include "vad.h" /* Constants of VAD hangover addition */ #define HANGCONST 10 #define BURSTCONST 3 /* Constant of spectral comparison */ #define STAT_THRESH 3670L /* 0.056 */ /* Constants of periodicity detection */ #define LTHRESH 2 #define NTHRESH 4 /* Pseudo floating point representations of constants for threshold adaptation */ #define M_PTH 32500 /*** 130000.0 ***/ #define E_PTH 17 #define M_PLEV 21667 /*** 346666.7 ***/ #define E_PLEV 19 #define M_MARGIN 16927 /*** 69333340 ***/ #define E_MARGIN 27 #define FAC 17203 /* 2.1 */ /* Constants of tone detection */ #define FREQTH 3189 #define PREDTH 1464 /* Static variables of VAD */ static Word16 rvad[9], scal_rvad; static Pfloat thvad; static Word32 L_sacf[27]; static Word32 L_sav0[36]; static Word16 pt_sacf, pt_sav0; static Word32 L_lastdm; static Word16 adaptcount; static Word16 burstcount, hangcount; static Word16 oldlagcount, veryoldlagcount, oldlag; Word16 ptch; /************************************************************************* * * FUNCTION NAME: vad_reset * * PURPOSE: Resets the static variables of the VAD to their * initial values * *************************************************************************/ void vad_reset () { Word16 i; /* Initialize rvad variables */ rvad[0] = 0x6000; for (i = 1; i < 9; i++) { rvad[i] = 0; } scal_rvad = 7; /* Initialize threshold level */ thvad.e = 20; /*** exponent ***/ thvad.m = 27083; /*** mantissa ***/ /* Initialize ACF averaging variables */ for (i = 0; i < 27; i++) { L_sacf[i] = 0L; } for (i = 0; i < 36; i++) { L_sav0[i] = 0L; } pt_sacf = 0; pt_sav0 = 0; /* Initialize spectral comparison variable */ L_lastdm = 0L; /* Initialize threshold adaptation variable */ adaptcount = 0; /* Initialize VAD hangover addition variables */ burstcount = 0; hangcount = -1; /* Initialize periodicity detection variables */ oldlagcount = 0; veryoldlagcount = 0; oldlag = 18; ptch = 1; return; } /**************************************************************************** * * FUNCTION: vad_computation * * PURPOSE: Returns a decision as to whether the current frame being * processed by the speech encoder contains speech or not. * * INPUTS: r_h[0..8] autocorrelation of input signal frame (msb) * r_l[0..8] autocorrelation of input signal frame (lsb) * scal_acf scaling factor for the autocorrelations * rc[0..3] speech encoder reflection coefficients * ptch flag to indicate a periodic signal component * * OUTPUTS: none * * RETURN VALUE: vad decision * ***************************************************************************/ Word16 vad_computation ( Word16 r_h[], Word16 r_l[], Word16 scal_acf, Word16 rc[], Word16 ptch ) { Word32 L_av0[9], L_av1[9]; Word16 vad, vvad, rav1[9], scal_rav1, stat, tone; Pfloat acf0, pvad; energy_computation (r_h, scal_acf, rvad, scal_rvad, &acf0, &pvad); acf_averaging (r_h, r_l, scal_acf, L_av0, L_av1); predictor_values (L_av1, rav1, &scal_rav1); stat = spectral_comparison (rav1, scal_rav1, L_av0); move16 (); tone_detection (rc, &tone); threshold_adaptation (stat, ptch, tone, rav1, scal_rav1, pvad, acf0, rvad, &scal_rvad, &thvad); vvad = vad_decision (pvad, thvad); move16 (); vad = vad_hangover (vvad); move16 (); return vad; } /**************************************************************************** * * FUNCTION: energy_computation * * PURPOSE: Computes the input and residual energies of the adaptive * filter in a floating point representation. * * INPUTS: r_h[0..8] autocorrelation of input signal frame (msb) * scal_acf scaling factor for the autocorrelations * rvad[0..8] autocorrelated adaptive filter coefficients * scal_rvad scaling factor for rvad[] * * OUTPUTS: *acf0 signal frame energy (mantissa+exponent) * *pvad filtered signal energy (mantissa+exponent) * * RETURN VALUE: none * ***************************************************************************/ void energy_computation ( Word16 r_h[], Word16 scal_acf, Word16 rvad[], Word16 scal_rvad, Pfloat * acf0, Pfloat * pvad ) { Word16 i, temp, norm_prod; Word32 L_temp; /* r[0] is always greater than zero (no need to test for r[0] == 0) */ /* Computation of acf0 (exponent and mantissa) */ acf0->e = sub (32, scal_acf); move16 (); acf0->m = r_h[0] & 0x7ff8; move16 (); logic16 (); /* Computation of pvad (exponent and mantissa) */ pvad->e = add (acf0->e, 14); move16 (); pvad->e = sub (pvad->e, scal_rvad); move16 (); L_temp = 0L; move32 (); for (i = 1; i <= 8; i++) { temp = shr (r_h[i], 3); L_temp = L_mac (L_temp, temp, rvad[i]); } temp = shr (r_h[0], 3); L_temp = L_add (L_temp, L_shr (L_mult (temp, rvad[0]), 1)); test (); if (L_temp <= 0L) { L_temp = 1L; move32 (); } norm_prod = norm_l (L_temp); pvad->e = sub (pvad->e, norm_prod); move16 (); pvad->m = extract_h (L_shl (L_temp, norm_prod)); move16 (); return; } /**************************************************************************** * * FUNCTION: acf_averaging * * PURPOSE: Computes the arrays L_av0[0..8] and L_av1[0..8]. * * INPUTS: r_h[0..8] autocorrelation of input signal frame (msb) * r_l[0..8] autocorrelation of input signal frame (lsb) * scal_acf scaling factor for the autocorrelations * * OUTPUTS: L_av0[0..8] ACF averaged over last four frames * L_av1[0..8] ACF averaged over previous four frames * * RETURN VALUE: none * ***************************************************************************/ void acf_averaging ( Word16 r_h[], Word16 r_l[], Word16 scal_acf, Word32 L_av0[], Word32 L_av1[] ) { Word32 L_temp; Word16 scale; Word16 i; scale = add (9, scal_acf); for (i = 0; i <= 8; i++) { L_temp = L_shr (L_Comp (r_h[i], r_l[i]), scale); L_av0[i] = L_add (L_sacf[i], L_temp); move32 (); L_av0[i] = L_add (L_sacf[i + 9], L_av0[i]); move32 (); L_av0[i] = L_add (L_sacf[i + 18], L_av0[i]); move32 (); L_sacf[pt_sacf + i] = L_temp; move32 (); L_av1[i] = L_sav0[pt_sav0 + i]; move32 (); L_sav0[pt_sav0 + i] = L_av0[i]; move32 (); } /* Update the array pointers */ test (); if (sub (pt_sacf, 18) == 0) { pt_sacf = 0; move16 (); } else { pt_sacf = add (pt_sacf, 9); } test (); if (sub (pt_sav0, 27) == 0) { pt_sav0 = 0; move16 (); } else { pt_sav0 = add (pt_sav0, 9); } return; } /**************************************************************************** * * FUNCTION: predictor_values * * PURPOSE: Computes the array rav[0..8] needed for the spectral * comparison and the threshold adaptation. * * INPUTS: L_av1[0..8] ACF averaged over previous four frames * * OUTPUTS: rav1[0..8] ACF obtained from L_av1 * *scal_rav1 rav1[] scaling factor * * RETURN VALUE: none * ***************************************************************************/ void predictor_values ( Word32 L_av1[], Word16 rav1[], Word16 *scal_rav1 ) { Word16 vpar[8], aav1[9]; schur_recursion (L_av1, vpar); step_up (8, vpar, aav1); compute_rav1 (aav1, rav1, scal_rav1); return; } /**************************************************************************** * * FUNCTION: schur_recursion * * PURPOSE: Uses the Schur recursion to compute adaptive filter * reflection coefficients from an autorrelation function. * * INPUTS: L_av1[0..8] autocorrelation function * * OUTPUTS: vpar[0..7] reflection coefficients * * RETURN VALUE: none * ***************************************************************************/ void schur_recursion ( Word32 L_av1[], Word16 vpar[] ) { Word16 acf[9], pp[9], kk[9], temp; Word16 i, k, m, n; /*** Schur recursion with 16-bit arithmetic ***/ test (); move32 (); if (L_av1[0] == 0) { for (i = 0; i < 8; i++) { vpar[i] = 0; move16 (); } return; } temp = norm_l (L_av1[0]); for (k = 0; k <= 8; k++) { acf[k] = extract_h (L_shl (L_av1[k], temp)); move16 (); } /*** Initialize arrays pp[..] and kk[..] for the recursion: ***/ for (i = 1; i <= 7; i++) { kk[9 - i] = acf[i]; move16 (); } for (i = 0; i <= 8; i++) { pp[i] = acf[i]; move16 (); } /*** Compute Parcor coefficients: ***/ for (n = 0; n < 8; n++) { test (); if ((pp[0] == 0) || (sub (pp[0], abs_s (pp[1])) < 0)) { for (i = n; i < 8; i++) { vpar[i] = 0; move16 (); } return; } vpar[n] = div_s (abs_s (pp[1]), pp[0]); move16 (); test (); move16 (); if (pp[1] > 0) { vpar[n] = negate (vpar[n]); move16 (); } test (); if (sub (n, 7) == 0) { return; } /*** Schur recursion: ***/ pp[0] = add (pp[0], mult_r (pp[1], vpar[n])); move16 (); for (m = 1; m <= 7 - n; m++) { pp[m] = add (pp[1 + m], mult_r (kk[9 - m], vpar[n])); move16 (); kk[9 - m] = add (kk[9 - m], mult_r (pp[1 + m], vpar[n])); move16 (); } } return; } /**************************************************************************** * * FUNCTION: step_up * * PURPOSE: Computes the transversal filter coefficients from the * reflection coefficients. * * INPUTS: np filter order (2..8) * vpar[0..np-1] reflection coefficients * * OUTPUTS: aav1[0..np] transversal filter coefficients * * RETURN VALUE: none * ***************************************************************************/ void step_up ( Word16 np, Word16 vpar[], Word16 aav1[] ) { Word32 L_coef[9], L_work[9]; Word16 temp; Word16 i, m; /*** Initialization of the step-up recursion ***/ L_coef[0] = 0x20000000L; move32 (); L_coef[1] = L_shl (L_deposit_l (vpar[0]), 14); move32 (); /*** Loop on the LPC analysis order: ***/ for (m = 2; m <= np; m++) { for (i = 1; i < m; i++) { temp = extract_h (L_coef[m - i]); L_work[i] = L_mac (L_coef[i], vpar[m - 1], temp); move32 (); } for (i = 1; i < m; i++) { L_coef[i] = L_work[i]; move32 (); } L_coef[m] = L_shl (L_deposit_l (vpar[m - 1]), 14); move32 (); } /*** Keep the aav1[0..np] in 15 bits ***/ for (i = 0; i <= np; i++) { aav1[i] = extract_h (L_shr (L_coef[i], 3)); move32 (); } return; } /**************************************************************************** * * FUNCTION: compute_rav1 * * PURPOSE: Computes the autocorrelation function of the adaptive * filter coefficients. * * INPUTS: aav1[0..8] adaptive filter coefficients * * OUTPUTS: rav1[0..8] ACF of aav1 * *scal_rav1 rav1[] scaling factor * * RETURN VALUE: none * ***************************************************************************/ void compute_rav1 ( Word16 aav1[], Word16 rav1[], Word16 *scal_rav1 ) { Word32 L_work[9]; Word16 i, k; /*** Computation of the rav1[0..8] ***/ for (i = 0; i <= 8; i++) { L_work[i] = 0L; move32 (); for (k = 0; k <= 8 - i; k++) { L_work[i] = L_mac (L_work[i], aav1[k], aav1[k + i]); move32 (); } } test (); move32 (); if (L_work[0] == 0L) { *scal_rav1 = 0; move16 (); } else { *scal_rav1 = norm_l (L_work[0]); } for (i = 0; i <= 8; i++) { rav1[i] = extract_h (L_shl (L_work[i], *scal_rav1)); move16 (); } return; } /**************************************************************************** * * FUNCTION: spectral_comparison * * PURPOSE: Computes the stat flag needed for the threshold * adaptation decision. * * INPUTS: rav1[0..8] ACF obtained from L_av1 * *scal_rav1 rav1[] scaling factor * L_av0[0..8] ACF averaged over last four frames * * OUTPUTS: none * * RETURN VALUE: flag to indicate spectral stationarity * ***************************************************************************/ Word16 spectral_comparison ( Word16 rav1[], Word16 scal_rav1, Word32 L_av0[] ) { Word32 L_dm, L_sump, L_temp; Word16 stat, sav0[9], shift, divshift, temp; Word16 i; /*** Re-normalize L_av0[0..8] ***/ test (); move32 (); if (L_av0[0] == 0L) { for (i = 0; i <= 8; i++) { sav0[i] = 0x0fff; /* 4095 */ move16 (); } } else { shift = sub (norm_l (L_av0[0]), 3); for (i = 0; i <= 8; i++) { sav0[i] = extract_h (L_shl (L_av0[i], shift)); move16 (); } } /*** Compute partial sum of dm ***/ L_sump = 0L; move32 (); for (i = 1; i <= 8; i++) { L_sump = L_mac (L_sump, rav1[i], sav0[i]); } /*** Compute the division of the partial sum by sav0[0] ***/ test (); if (L_sump < 0L) { L_temp = L_negate (L_sump); } else { L_temp = L_sump; move32 (); } test (); if (L_temp == 0L) { L_dm = 0L; move32 (); shift = 0; move16 (); } else { sav0[0] = shl (sav0[0], 3); move16 (); shift = norm_l (L_temp); temp = extract_h (L_shl (L_temp, shift)); test (); if (sub (sav0[0], temp) >= 0) { divshift = 0; move16 (); temp = div_s (temp, sav0[0]); } else { divshift = 1; move16 (); temp = sub (temp, sav0[0]); temp = div_s (temp, sav0[0]); } test (); if (sub (divshift, 1) == 0) { L_dm = 0x8000L; move32 (); } else { L_dm = 0L; move32 (); } L_dm = L_shl (L_add (L_dm, L_deposit_l (temp)), 1); test (); if (L_sump < 0L) { L_dm = L_negate (L_dm); } } /*** Re-normalization and final computation of L_dm ***/ L_dm = L_shl (L_dm, 14); L_dm = L_shr (L_dm, shift); L_dm = L_add (L_dm, L_shl (L_deposit_l (rav1[0]), 11)); L_dm = L_shr (L_dm, scal_rav1); /*** Compute the difference and save L_dm ***/ L_temp = L_sub (L_dm, L_lastdm); L_lastdm = L_dm; move32 (); test (); if (L_temp < 0L) { L_temp = L_negate (L_temp); } /*** Evaluation of the stat flag ***/ L_temp = L_sub (L_temp, STAT_THRESH); test (); if (L_temp < 0L) { stat = 1; move16 (); } else { stat = 0; move16 (); } return stat; } /**************************************************************************** * * FUNCTION: threshold_adaptation * * PURPOSE: Evaluates the secondary VAD decision. If speech is not * present then the noise model rvad and adaptive threshold * thvad are updated. * * INPUTS: stat flag to indicate spectral stationarity * ptch flag to indicate a periodic signal component * tone flag to indicate a tone signal component * rav1[0..8] ACF obtained from L_av1 * scal_rav1 rav1[] scaling factor * pvad filtered signal energy (mantissa+exponent) * acf0 signal frame energy (mantissa+exponent) * * OUTPUTS: rvad[0..8] autocorrelated adaptive filter coefficients * *scal_rvad rvad[] scaling factor * *thvad decision threshold (mantissa+exponent) * * RETURN VALUE: none * ***************************************************************************/ void threshold_adaptation ( Word16 stat, Word16 ptch, Word16 tone, Word16 rav1[], Word16 scal_rav1, Pfloat pvad, Pfloat acf0, Word16 rvad[], Word16 *scal_rvad, Pfloat * thvad ) { Word16 comp, comp2; Word32 L_temp; Word16 temp; Pfloat p_temp; Word16 i; comp = 0; move16 (); /*** Test if acf0 < pth; if yes set thvad to plev ***/ test (); if (sub (acf0.e, E_PTH) < 0) { comp = 1; move16 (); } test (); test (); if ((sub (acf0.e, E_PTH) == 0) && (sub (acf0.m, M_PTH) < 0)) { comp = 1; move16 (); } test (); if (sub (comp, 1) == 0) { thvad->e = E_PLEV; move16 (); thvad->m = M_PLEV; move16 (); return; } /*** Test if an adaption is required ***/ test (); if (sub (ptch, 1) == 0) { comp = 1; move16 (); } test (); if (stat == 0) { comp = 1; move16 (); } test (); if (sub (tone, 1) == 0) { comp = 1; move16 (); } test (); if (sub (comp, 1) == 0) { adaptcount = 0; move16 (); return; } /*** Increment adaptcount ***/ adaptcount = add (adaptcount, 1); test (); if (sub (adaptcount, 8) <= 0) { return; } /*** computation of thvad-(thvad/dec) ***/ thvad->m = sub (thvad->m, shr (thvad->m, 5)); move16 (); test (); if (sub (thvad->m, 0x4000) < 0) { thvad->m = shl (thvad->m, 1); move16 (); thvad->e = sub (thvad->e, 1); move16 (); } /*** computation of pvad*fac ***/ L_temp = L_mult (pvad.m, FAC); L_temp = L_shr (L_temp, 15); p_temp.e = add (pvad.e, 1); move16 (); test (); if (L_temp > 0x7fffL) { L_temp = L_shr (L_temp, 1); p_temp.e = add (p_temp.e, 1); move16 (); } p_temp.m = extract_l (L_temp); move16 (); /*** test if thvad < pvad*fac ***/ test (); if (sub (thvad->e, p_temp.e) < 0) { comp = 1; move16 (); } test (); test (); if ((sub (thvad->e, p_temp.e) == 0) && (sub (thvad->m, p_temp.m) < 0)) { comp = 1; move16 (); } /*** compute minimum(thvad+(thvad/inc), pvad*fac) when comp = 1 ***/ test (); if (sub (comp, 1) == 0) { /*** compute thvad + (thvad/inc) ***/ L_temp = L_add (L_deposit_l (thvad->m), L_deposit_l (shr (thvad->m, 4))); test (); if (L_sub (L_temp, 0x7fffL) > 0) { thvad->m = extract_l (L_shr (L_temp, 1)); move16 (); thvad->e = add (thvad->e, 1); move16 (); } else { thvad->m = extract_l (L_temp); move16 (); } comp2 = 0; move16 (); test (); if (sub (p_temp.e, thvad->e) < 0) { comp2 = 1; move16 (); } test (); test (); if ((sub (p_temp.e, thvad->e) == 0) && (sub (p_temp.m, thvad->m) < 0)) { comp2 = 1; move16 (); } test (); if (sub (comp2, 1) == 0) { thvad->e = p_temp.e;move16 (); thvad->m = p_temp.m;move16 (); } } /*** compute pvad + margin ***/ test (); if (sub (pvad.e, E_MARGIN) == 0) { L_temp = L_add (L_deposit_l (pvad.m), L_deposit_l (M_MARGIN)); p_temp.m = extract_l (L_shr (L_temp, 1)); move16 (); p_temp.e = add (pvad.e, 1); move16 (); } else { test (); if (sub (pvad.e, E_MARGIN) > 0) { temp = sub (pvad.e, E_MARGIN); temp = shr (M_MARGIN, temp); L_temp = L_add (L_deposit_l (pvad.m), L_deposit_l (temp)); test (); if (L_sub (L_temp, 0x7fffL) > 0) { p_temp.e = add (pvad.e, 1); move16 (); p_temp.m = extract_l (L_shr (L_temp, 1)); move16 (); } else { p_temp.e = pvad.e; move16 (); p_temp.m = extract_l (L_temp); move16 (); } } else { temp = sub (E_MARGIN, pvad.e); temp = shr (pvad.m, temp); L_temp = L_add (L_deposit_l (M_MARGIN), L_deposit_l (temp)); test (); if (L_sub (L_temp, 0x7fffL) > 0) { p_temp.e = add (E_MARGIN, 1); move16 (); p_temp.m = extract_l (L_shr (L_temp, 1)); move16 (); } else { p_temp.e = E_MARGIN; move16 (); p_temp.m = extract_l (L_temp); move16 (); } } } /*** Test if thvad > pvad + margin ***/ comp = 0; move16 (); test (); if (sub (thvad->e, p_temp.e) > 0) { comp = 1; move16 (); } test (); test (); if ((sub (thvad->e, p_temp.e) == 0) && (sub (thvad->m, p_temp.m) > 0)) { comp = 1; move16 (); } test (); if (sub (comp, 1) == 0) { thvad->e = p_temp.e; move16 (); thvad->m = p_temp.m; move16 (); } /*** Normalise and retain rvad[0..8] in memory ***/ *scal_rvad = scal_rav1; move16 (); for (i = 0; i <= 8; i++) { rvad[i] = rav1[i]; move16 (); } /*** Set adaptcount to adp + 1 ***/ adaptcount = 9; move16 (); return; } /**************************************************************************** * * FUNCTION: tone_detection * * PURPOSE: Computes the tone flag needed for the threshold * adaptation decision. * * INPUTS: rc[0..3] reflection coefficients calculated in the * speech encoder short term predictor * * OUTPUTS: *tone flag to indicate a periodic signal component * * RETURN VALUE: none * ***************************************************************************/ void tone_detection ( Word16 rc[], Word16 *tone ) { Word32 L_num, L_den, L_temp; Word16 temp, prederr, a[3]; Word16 i; *tone = 0; move16 (); /*** Calculate filter coefficients ***/ step_up (2, rc, a); /*** Calculate ( a[1] * a[1] ) ***/ temp = shl (a[1], 3); L_den = L_mult (temp, temp); /*** Calculate ( 4*a[2] - a[1]*a[1] ) ***/ L_temp = L_shl (L_deposit_h (a[2]), 3); L_num = L_sub (L_temp, L_den); /*** Check if pole frequency is less than 385 Hz ***/ test (); if (L_num <= 0) { return; } test (); move16 (); if (a[1] < 0) { temp = extract_h (L_den); L_den = L_mult (temp, FREQTH); L_temp = L_sub (L_num, L_den); test (); if (L_temp < 0) { return; } } /*** Calculate normalised prediction error ***/ prederr = 0x7fff; move16 (); for (i = 0; i < 4; i++) { temp = mult (rc[i], rc[i]); temp = sub (0x7fff, temp); prederr = mult (prederr, temp); } /*** Test if prediction error is smaller than threshold ***/ temp = sub (prederr, PREDTH); test (); if (temp < 0) { *tone = 1; move16 (); } return; } /**************************************************************************** * * FUNCTION: vad_decision * * PURPOSE: Computes the VAD decision based on the comparison of the * floating point representations of pvad and thvad. * * INPUTS: pvad filtered signal energy (mantissa+exponent) * thvad decision threshold (mantissa+exponent) * * OUTPUTS: none * * RETURN VALUE: vad decision before hangover is added * ***************************************************************************/ Word16 vad_decision ( Pfloat pvad, Pfloat thvad ) { Word16 vvad; test (); test (); test (); if (sub (pvad.e, thvad.e) > 0) { vvad = 1; move16 (); } else if ((sub (pvad.e, thvad.e) == 0) && (sub (pvad.m, thvad.m) > 0)) { vvad = 1; move16 (); } else { vvad = 0; move16 (); } return vvad; } /**************************************************************************** * * FUNCTION: vad_hangover * * PURPOSE: Computes the final VAD decision for the current frame * being processed. * * INPUTS: vvad vad decision before hangover is added * * OUTPUTS: none * * RETURN VALUE: vad decision after hangover is added * ***************************************************************************/ Word16 vad_hangover ( Word16 vvad ) { test (); if (sub (vvad, 1) == 0) { burstcount = add (burstcount, 1); } else { burstcount = 0; move16 (); } test (); if (sub (burstcount, BURSTCONST) >= 0) { hangcount = HANGCONST; move16 (); burstcount = BURSTCONST;move16 (); } test (); if (hangcount >= 0) { hangcount = sub (hangcount, 1); return 1; /* vad = 1 */ } return vvad; /* vad = vvad */ } /**************************************************************************** * * FUNCTION: periodicity_update * * PURPOSE: Computes the ptch flag needed for the threshold * adaptation decision for the next frame. * * INPUTS: lags[0..1] speech encoder long term predictor lags * * OUTPUTS: *ptch Boolean voiced / unvoiced decision * * RETURN VALUE: none * ***************************************************************************/ void periodicity_update ( Word16 lags[], Word16 *ptch ) { Word16 minlag, maxlag, lagcount, temp; Word16 i; /*** Run loop for the two halves in the frame ***/ lagcount = 0; move16 (); for (i = 0; i <= 1; i++) { /*** Search the maximum and minimum of consecutive lags ***/ test (); if (sub (oldlag, lags[i]) > 0) { minlag = lags[i]; move16 (); maxlag = oldlag; move16 (); } else { minlag = oldlag; move16 (); maxlag = lags[i]; move16 (); } temp = sub (maxlag, minlag); test (); if (sub (temp, LTHRESH) < 0) { lagcount = add (lagcount, 1); } /*** Save the current LTP lag ***/ oldlag = lags[i]; move16 (); } /*** Update the veryoldlagcount and oldlagcount ***/ veryoldlagcount = oldlagcount; move16 (); oldlagcount = lagcount; move16 (); /*** Make ptch decision ready for next frame ***/ temp = add (oldlagcount, veryoldlagcount); test (); if (sub (temp, NTHRESH) >= 0) { *ptch = 1; move16 (); } else { *ptch = 0; move16 (); } return; }