/*
********************************************************************************
* PRIVATE PROGRAM CODE
********************************************************************************
*/
void MR475_quant_store_results(
gc_predState *pred_st, /* i/o: gain predictor state struct */
const Word16 *p, /* i : pointer to selected quantizer table entry */
Word16 gcode0, /* i : predicted CB gain, Q(14 - exp_gcode0) */
Word16 exp_gcode0, /* i : exponent of predicted CB gain, Q0 */
Word16 *gain_pit, /* o : Pitch gain, Q14 */
Word16 *gain_cod /* o : Code gain, Q1 */
)
{
Word16 g_code, exp, frac, tmp;
Word32 L_tmp;
Word16 qua_ener_MR122; /* o : quantized energy error, MR122 version Q10 */
Word16 qua_ener; /* o : quantized energy error, Q10 */
/* Read the quantized gains */
*gain_pit = *p++;
g_code = *p++;
/*------------------------------------------------------------------*
* calculate final fixed codebook gain: *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* *
* gc = gc0 * g *
*------------------------------------------------------------------*/
L_tmp = L_mult(g_code, gcode0);
L_tmp = L_shr(L_tmp, sub(10, exp_gcode0));
*gain_cod = extract_h(L_tmp);
/*------------------------------------------------------------------*
* calculate predictor update values and update gain predictor: *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* *
* qua_ener = log2(g) *
* qua_ener_MR122 = 20*log10(g) *
*------------------------------------------------------------------*/
Log2 (L_deposit_l (g_code), &exp, &frac); /* Log2(x Q12) = log2(x) + 12 */
exp = sub(exp, 12);
tmp = shr_r (frac, 5);
qua_ener_MR122 = add (tmp, shl (exp, 10));
L_tmp = Mpy_32_16(exp, frac, 24660); /* 24660 Q12 ~= 6.0206 = 20*log10(2) */
qua_ener = round (L_shl (L_tmp, 13)); /* Q12 * Q0 = Q13 -> Q10 */
gc_pred_update(pred_st, qua_ener_MR122, qua_ener);
}
/*************************************************************************
*
* FUNCTION: Dec_gain()
*
* PURPOSE: Decode the pitch and codebook gains
*
************************************************************************/
void Dec_gain(
gc_predState *pred_state, /* i/o: MA predictor state */
enum Mode mode, /* i : AMR mode */
Word16 index, /* i : index of quantization. */
Word16 code[], /* i : Innovative vector. */
Word16 evenSubfr, /* i : Flag for even subframes */
Word16 * gain_pit, /* o : Pitch gain. */
Word16 * gain_cod /* o : Code gain. */
)
{
const Word16 *p;
Word16 frac, gcode0, exp, qua_ener, qua_ener_MR122;
Word16 g_code;
Word32 L_tmp;
/* Read the quantized gains (table depends on mode) */
index = shl (index, 2);
test(); test(); test();
if ( sub (mode, MR102) == 0
|| sub (mode, MR74) == 0
|| sub (mode, MR67) == 0)
{
p = &table_gain_highrates[index]; move16 ();
*gain_pit = *p++; move16 ();
g_code = *p++; move16 ();
qua_ener_MR122 = *p++; move16 ();
qua_ener = *p; move16 ();
}
else
{
test();
if (sub (mode, MR475) == 0)
{
index = add (index, shl(sub(1, evenSubfr), 1));
p = &table_gain_MR475[index]; move16 ();
*gain_pit = *p++; move16 ();
g_code = *p++; move16 ();
/*---------------------------------------------------------*
* calculate predictor update values (not stored in 4.75 *
* quantizer table to save space): *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* *
* qua_ener = log2(g) *
* qua_ener_MR122 = 20*log10(g) *
*---------------------------------------------------------*/
/* Log2(x Q12) = log2(x) + 12 */
Log2 (L_deposit_l (g_code), &exp, &frac);
exp = sub(exp, 12);
qua_ener_MR122 = add (shr_r (frac, 5), shl (exp, 10));
/* 24660 Q12 ~= 6.0206 = 20*log10(2) */
L_tmp = Mpy_32_16(exp, frac, 24660);
qua_ener = round (L_shl (L_tmp, 13)); /* Q12 * Q0 = Q13 -> Q10 */
}
else
{
p = &table_gain_lowrates[index]; move16 ();
*gain_pit = *p++; move16 ();
g_code = *p++; move16 ();
qua_ener_MR122 = *p++; move16 ();
qua_ener = *p; move16 ();
}
}
/*-------------------------------------------------------------------*
* predict codebook gain *
* ~~~~~~~~~~~~~~~~~~~~~ *
* gc0 = Pow2(int(d)+frac(d)) *
* = 2^exp + 2^frac *
* *
* gcode0 (Q14) = 2^14*2^frac = gc0 * 2^(14-exp) *
*-------------------------------------------------------------------*/
gc_pred(pred_state, mode, code, &exp, &frac, NULL, NULL);
gcode0 = extract_l(Pow2(14, frac));
/*------------------------------------------------------------------*
* read quantized gains, update table of past quantized energies *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* st->past_qua_en(Q10) = 20 * Log10(g_fac) / constant *
* = Log2(g_fac) *
* = qua_ener *
* constant = 20*Log10(2) *
*------------------------------------------------------------------*/
L_tmp = L_mult(g_code, gcode0);
L_tmp = L_shr(L_tmp, sub(10, exp));
*gain_cod = extract_h(L_tmp);
/* update table of past quantized energies */
gc_pred_update(pred_state, qua_ener_MR122, qua_ener);
return;
}
/*************************************************************************
*
* Function: gain_adapt()
* Purpose: calculate pitch/codebook gain adaptation factor alpha
* (and update the adaptor state)
*
**************************************************************************
*/
void gain_adapt(
GainAdaptState *st, /* i : state struct */
Word16 ltpg, /* i : ltp coding gain (log2()), Q13 */
Word16 gain_cod, /* i : code gain, Q1 */
Word16 *alpha /* o : gain adaptation factor, Q15 */
)
{
Word16 adapt; /* adaptdation status; 0, 1, or 2 */
Word16 result; /* alpha factor, Q13 */
Word16 filt; /* median-filtered LTP coding gain, Q13 */
Word16 tmp, i;
/* basic adaptation */
if (sub (ltpg, LTP_GAIN_THR1) <= 0)
{
adapt = 0;
}
else
{
if (sub (ltpg, LTP_GAIN_THR2) <= 0)
{
adapt = 1;
}
else
{
adapt = 2;
}
}
/*
* // onset indicator
* if ((cbGain > onFact * cbGainMem[0]) && (cbGain > 100.0))
* onset = 8;
* else
* if (onset)
* onset--;
*/
/* tmp = cbGain / onFact; onFact = 2.0; 200 Q1 = 100.0 */
tmp = shr_r (gain_cod, 1);
if ((sub (tmp, st->prev_gc) > 0) && sub(gain_cod, 200) > 0)
{
st->onset = 8;
}
else
{
if (st->onset != 0)
{
st->onset = sub (st->onset, 1);
}
}
/*
* // if onset, increase adaptor state
* if (onset && (gainAdapt < 2)) gainAdapt++;
*/
if ((st->onset != 0) && (sub (adapt, 2) < 0))
{
adapt = add (adapt, 1);
}
st->ltpg_mem[0] = ltpg;
filt = gmed_n (st->ltpg_mem, 5); /* function result */
if (adapt == 0)
{
if (sub (filt, 5443) > 0) /* 5443 Q13 = 0.66443... */
{
result = 0;
}
else
{
if (filt < 0)
{
result = 16384; /* 16384 Q15 = 0.5 */
}
else
{ /* result = 0.5 - 0.75257499*filt */
/* result (Q15) = 16384 - 24660 * (filt << 2) */
filt = shl (filt, 2); /* Q15 */
result = sub (16384, mult (24660, filt));
}
}
}
else
{
result = 0;
}
/*
* if (prevAlpha == 0.0) result = 0.5 * (result + prevAlpha);
*/
if (st->prev_alpha == 0)
{
result = shr (result, 1);
}
/* store the result */
*alpha = result;
/* update adapter state memory */
st->prev_alpha = result;
st->prev_gc = gain_cod;
for (i = LTPG_MEM_SIZE-1; i > 0; i--)
{
st->ltpg_mem[i] = st->ltpg_mem[i-1];
}
/* mem[0] is just present for convenience in calling the gmed_n[5]
* function above. The memory depth is really LTPG_MEM_SIZE-1.
*/
}
/*-----------------------------------------------------------*
* procedure Calc_exc_rand *
* ~~~~~~~~~~~~~ *
* Computes comfort noise excitation *
* for SID and not-transmitted frames *
*-----------------------------------------------------------*/
void Calc_exc_rand(
Word32 L_exc_err[4],
Word16 cur_gain, /* (i) : target sample gain */
Word16 *exc, /* (i/o) : excitation array */
Word16 *seed, /* (i) : current Vad decision */
Flag flag_cod /* (i) : encoder/decoder flag */
)
{
Word16 i, j, i_subfr;
Word16 temp1, temp2;
Word16 pos[4];
Word16 sign[4];
Word16 t0, frac;
Word16 *cur_exc;
Word16 g, Gp, Gp2;
Word16 excg[L_SUBFR], excs[L_SUBFR];
Word32 L_acc, L_ener, L_k;
Word16 max, hi, lo, inter_exc;
Word16 sh;
Word16 x1, x2;
if(cur_gain == 0) {
for(i=0; i<L_FRAME; i++) {
exc[i] = 0;
}
Gp = 0;
t0 = add(L_SUBFR,1);
for (i_subfr = 0; i_subfr < L_FRAME; i_subfr += L_SUBFR) {
if(flag_cod != FLAG_DEC) update_exc_err(L_exc_err, Gp, t0);
}
return;
}
/* Loop on subframes */
cur_exc = exc;
for (i_subfr = 0; i_subfr < L_FRAME; i_subfr += L_SUBFR) {
/* generate random adaptive codebook & fixed codebook parameters */
/*****************************************************************/
temp1 = Random(seed);
frac = sub((temp1 & (Word16)0x0003), 1);
if(sub(frac, 2) == 0) frac = 0;
temp1 = shr(temp1, 2);
t0 = add((temp1 & (Word16)0x003F), 40);
temp1 = shr(temp1, 6);
temp2 = temp1 & (Word16)0x0007;
pos[0] = add(shl(temp2, 2), temp2); /* 5 * temp2 */
temp1 = shr(temp1, 3);
sign[0] = temp1 & (Word16)0x0001;
temp1 = shr(temp1, 1);
temp2 = temp1 & (Word16)0x0007;
temp2 = add(shl(temp2, 2), temp2);
pos[1] = add(temp2, 1); /* 5 * x + 1 */
temp1 = shr(temp1, 3);
sign[1] = temp1 & (Word16)0x0001;
temp1 = Random(seed);
temp2 = temp1 & (Word16)0x0007;
temp2 = add(shl(temp2, 2), temp2);
pos[2] = add(temp2, 2); /* 5 * x + 2 */
temp1 = shr(temp1, 3);
sign[2] = temp1 & (Word16)0x0001;
temp1 = shr(temp1, 1);
temp2 = temp1 & (Word16)0x000F;
pos[3] = add((temp2 & (Word16)1), 3); /* j+3*/
temp2 = (shr(temp2, 1)) & (Word16)7;
temp2 = add(shl(temp2, 2), temp2); /* 5i */
pos[3] = add(pos[3], temp2);
temp1 = shr(temp1, 4);
sign[3] = temp1 & (Word16)0x0001;
Gp = Random(seed) & (Word16)0x1FFF; /* < 0.5 Q14 */
Gp2 = shl(Gp, 1); /* Q15 */
/* Generate gaussian excitation */
/********************************/
L_acc = 0L;
for(i=0; i<L_SUBFR; i++) {
temp1 = Gauss(seed);
L_acc = L_mac(L_acc, temp1, temp1);
excg[i] = temp1;
}
/*
Compute fact = alpha x cur_gain * sqrt(L_SUBFR / Eg)
with Eg = SUM(i=0->39) excg[i]^2
and alpha = 0.5
alpha x sqrt(L_SUBFR)/2 = 1 + FRAC1
*/
L_acc = Inv_sqrt(L_shr(L_acc,1)); /* Q30 */
L_Extract(L_acc, &hi, &lo);
/* cur_gain = cur_gainR << 3 */
temp1 = mult_r(cur_gain, FRAC1);
temp1 = add(cur_gain, temp1);
/* <=> alpha x cur_gainR x 2^2 x sqrt(L_SUBFR) */
L_acc = Mpy_32_16(hi, lo, temp1); /* fact << 17 */
sh = norm_l(L_acc);
temp1 = extract_h(L_shl(L_acc, sh)); /* fact << (sh+1) */
sh = sub(sh, 14);
for(i=0; i<L_SUBFR; i++) {
temp2 = mult_r(excg[i], temp1);
temp2 = shr_r(temp2, sh); /* shl if sh < 0 */
excg[i] = temp2;
}
/* generate random adaptive excitation */
/****************************************/
Pred_lt_3(cur_exc, t0, frac, L_SUBFR);
/* compute adaptive + gaussian exc -> cur_exc */
/**********************************************/
max = 0;
for(i=0; i<L_SUBFR; i++) {
temp1 = mult_r(cur_exc[i], Gp2);
temp1 = add(temp1, excg[i]); /* may overflow */
cur_exc[i] = temp1;
temp1 = abs_s(temp1);
if(sub(temp1,max) > 0) max = temp1;
}
/* rescale cur_exc -> excs */
if(max == 0) sh = 0;
else {
sh = sub(3, norm_s(max));
if(sh <= 0) sh = 0;
}
for(i=0; i<L_SUBFR; i++) {
excs[i] = shr(cur_exc[i], sh);
}
/* Compute fixed code gain */
/***************************/
/**********************************************************/
/*** Solve EQ(X) = 4 X**2 + 2 b X + c */
/**********************************************************/
L_ener = 0L;
for(i=0; i<L_SUBFR; i++) {
L_ener = L_mac(L_ener, excs[i], excs[i]);
} /* ener x 2^(-2sh + 1) */
/* inter_exc = b >> sh */
inter_exc = 0;
for(i=0; i<4; i++) {
j = pos[i];
if(sign[i] == 0) {
inter_exc = sub(inter_exc, excs[j]);
}
else {
inter_exc = add(inter_exc, excs[j]);
}
}
/* Compute k = cur_gainR x cur_gainR x L_SUBFR */
L_acc = L_mult(cur_gain, L_SUBFR);
L_acc = L_shr(L_acc, 6);
temp1 = extract_l(L_acc); /* cur_gainR x L_SUBFR x 2^(-2) */
L_k = L_mult(cur_gain, temp1); /* k << 2 */
temp1 = add(1, shl(sh,1));
L_acc = L_shr(L_k, temp1); /* k x 2^(-2sh+1) */
/* Compute delta = b^2 - 4 c */
L_acc = L_sub(L_acc, L_ener); /* - 4 c x 2^(-2sh-1) */
inter_exc = shr(inter_exc, 1);
L_acc = L_mac(L_acc, inter_exc, inter_exc); /* 2^(-2sh-1) */
sh = add(sh, 1);
/* inter_exc = b x 2^(-sh) */
/* L_acc = delta x 2^(-2sh+1) */
if(L_acc < 0) {
/* adaptive excitation = 0 */
Copy(excg, cur_exc, L_SUBFR);
temp1 = abs_s(excg[(int)pos[0]]) | abs_s(excg[(int)pos[1]]);
temp2 = abs_s(excg[(int)pos[2]]) | abs_s(excg[(int)pos[3]]);
temp1 = temp1 | temp2;
sh = ((temp1 & (Word16)0x4000) == 0) ? (Word16)1 : (Word16)2;
inter_exc = 0;
for(i=0; i<4; i++) {
temp1 = shr(excg[(int)pos[i]], sh);
if(sign[i] == 0) {
inter_exc = sub(inter_exc, temp1);
}
else {
inter_exc = add(inter_exc, temp1);
}
} /* inter_exc = b >> sh */
L_Extract(L_k, &hi, &lo);
L_acc = Mpy_32_16(hi, lo, K0); /* k x (1- alpha^2) << 2 */
temp1 = sub(shl(sh, 1), 1); /* temp1 > 0 */
L_acc = L_shr(L_acc, temp1); /* 4k x (1 - alpha^2) << (-2sh+1) */
L_acc = L_mac(L_acc, inter_exc, inter_exc); /* delta << (-2sh+1) */
Gp = 0;
}
temp2 = Sqrt(L_acc); /* >> sh */
x1 = sub(temp2, inter_exc);
x2 = negate(add(inter_exc, temp2)); /* x 2^(-sh+2) */
if(sub(abs_s(x2),abs_s(x1)) < 0) x1 = x2;
temp1 = sub(2, sh);
g = shr_r(x1, temp1); /* shl if temp1 < 0 */
if(g >= 0) {
if(sub(g, G_MAX) > 0) g = G_MAX;
}
else {
if(add(g, G_MAX) < 0) g = negate(G_MAX);
}
/* Update cur_exc with ACELP excitation */
for(i=0; i<4; i++) {
j = pos[i];
if(sign[i] != 0) {
cur_exc[j] = add(cur_exc[j], g);
}
else {
cur_exc[j] = sub(cur_exc[j], g);
}
}
if(flag_cod != FLAG_DEC) update_exc_err(L_exc_err, Gp, t0);
cur_exc += L_SUBFR;
} /* end of loop on subframes */
return;
}
//=============================================================================
//函数名称:Dec_gain
//函数功能:解码的音调和码书增益
//=============================================================================
void Dec_gain(
gc_predState *pred_state, /* i/o: MA predictor state */
enum Mode mode, /* i : AMR mode */
Word16 index, /* i : index of quantization. */
Word16 code[], /* i : Innovative vector. */
Word16 evenSubfr, /* i : Flag for even subframes */
Word16 * gain_pit, /* o : Pitch gain. */
Word16 * gain_cod, /* o : Code gain. */
Flag * pOverflow
)
{
const Word16 *p;
Word16 frac;
Word16 gcode0;
Word16 exp;
Word16 qua_ener;
Word16 qua_ener_MR122;
Word16 g_code;
Word32 L_tmp;
Word16 temp1;
Word16 temp2;
/* Read the quantized gains (table depends on mode) */
//阅读量化收益（表取决于模式）
index = shl(index, 2, pOverflow);
if (mode == MR102 || mode == MR74 || mode == MR67)
{
p = &table_gain_highrates[index];
*gain_pit = *p++;
g_code = *p++;
qua_ener_MR122 = *p++;
qua_ener = *p;
}
else
{
if (mode == MR475)
{
index += (1 ^ evenSubfr) << 1; /* evenSubfr is 0 or 1 */
if (index > (MR475_VQ_SIZE*4 - 2))
{
index = (MR475_VQ_SIZE * 4 - 2); /* avoid possible buffer overflow */
}
p = &table_gain_MR475[index];
*gain_pit = *p++;
g_code = *p++;
/*---------------------------------------------------------*
* calculate predictor update values (not stored in 4.75 *
* quantizer table to save space): *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* *
* qua_ener = log2(g) *
* qua_ener_MR122 = 20*log10(g) *
*---------------------------------------------------------*/
//计算预测更新值（不存储在4.75量化表，以节省空间）
/* Log2(x Q12) = log2(x) + 12 */
temp1 = (Word16) L_deposit_l(g_code);
Log2(temp1, &exp, &frac, pOverflow);
exp = sub(exp, 12, pOverflow);
temp1 = shr_r(frac, 5, pOverflow);
temp2 = shl(exp, 10, pOverflow);
qua_ener_MR122 = add(temp1, temp2, pOverflow);
/* 24660 Q12 ~= 6.0206 = 20*log10(2) */
L_tmp = Mpy_32_16(exp, frac, 24660, pOverflow);
L_tmp = L_shl(L_tmp, 13, pOverflow);
qua_ener = pv_round(L_tmp, pOverflow);
/* Q12 * Q0 = Q13 -> Q10 */
}
else
{
p = &table_gain_lowrates[index];
*gain_pit = *p++;
g_code = *p++;
qua_ener_MR122 = *p++;
qua_ener = *p;
}
}
/*-------------------------------------------------------------------*
* predict codebook gain *
* ~~~~~~~~~~~~~~~~~~~~~ *
* gc0 = Pow2(int(d)+frac(d)) *
* = 2^exp + 2^frac *
* *
* gcode0 (Q14) = 2^14*2^frac = gc0 * 2^(14-exp) *
*-------------------------------------------------------------------*/
gc_pred(pred_state, mode, code, &exp, &frac, NULL, NULL, pOverflow);
gcode0 = (Word16) Pow2(14, frac, pOverflow);
/*------------------------------------------------------------------*
* read quantized gains, update table of past quantized energies *
* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *
* st->past_qua_en(Q10) = 20 * Log10(g_fac) / constant *
* = Log2(g_fac) *
* = qua_ener *
* constant = 20*Log10(2) *
*------------------------------------------------------------------*/
L_tmp = L_mult(g_code, gcode0, pOverflow);
temp1 = sub(10, exp, pOverflow);
L_tmp = L_shr(L_tmp, temp1, pOverflow);
*gain_cod = extract_h(L_tmp);
/* update table of past quantized energies */
//过去的量化能量表更新
gc_pred_update(pred_state, qua_ener_MR122, qua_ener);
return;
}
Word16 vad2 (Word16 * farray_ptr, vadState2 * st)
{
/*
* The channel table is defined below. In this table, the
* lower and higher frequency coefficients for each of the 16
* channels are specified. The table excludes the coefficients
* with numbers 0 (DC), 1, and 64 (Foldover frequency).
*/
const static Word16 ch_tbl[NUM_CHAN][2] =
{
{2, 3},
{4, 5},
{6, 7},
{8, 9},
{10, 11},
{12, 13},
{14, 16},
{17, 19},
{20, 22},
{23, 26},
{27, 30},
{31, 35},
{36, 41},
{42, 48},
{49, 55},
{56, 63}
};
/* channel energy scaling table - allows efficient division by number
* of DFT bins in the channel: 1/2, 1/3, 1/4, etc.
*/
const static Word16 ch_tbl_sh[NUM_CHAN] =
{
16384, 16384, 16384, 16384, 16384, 16384, 10923, 10923,
10923, 8192, 8192, 6554, 5461, 4681, 4681, 4096
};
/*
* The voice metric table is defined below. It is a non-
* linear table with a deadband near zero. It maps the SNR
* index (quantized SNR value) to a number that is a measure
* of voice quality.
*/
const static Word16 vm_tbl[90] =
{
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
3, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 7, 7, 7,
8, 8, 9, 9, 10, 10, 11, 12, 12, 13, 13, 14, 15,
15, 16, 17, 17, 18, 19, 20, 20, 21, 22, 23, 24,
24, 25, 26, 27, 28, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 37, 38, 39, 40, 41, 42, 43, 44, 45,
46, 47, 48, 49, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50
};
/* hangover as a function of peak SNR (3 dB steps) */
const static Word16 hangover_table[20] =
{
30, 30, 30, 30, 30, 30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 8, 8, 8
};
/* burst sensitivity as a function of peak SNR (3 dB steps) */
const static Word16 burstcount_table[20] =
{
8, 8, 8, 8, 8, 8, 8, 8, 7, 6, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4
};
/* voice metric sensitivity as a function of peak SNR (3 dB steps) */
const static Word16 vm_threshold_table[20] =
{
34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 34, 40, 51, 71, 100, 139, 191, 257, 337, 432
};
/* State tables that use 22,9 or 27,4 scaling for ch_enrg[] */
const static Word16 noise_floor_chan[2] = {NOISE_FLOOR_CHAN_0, NOISE_FLOOR_CHAN_1};
const static Word16 min_chan_enrg[2] = {MIN_CHAN_ENRG_0, MIN_CHAN_ENRG_1};
const static Word16 ine_noise[2] = {INE_NOISE_0, INE_NOISE_1};
const static Word16 fbits[2] = {FRACTIONAL_BITS_0, FRACTIONAL_BITS_1};
const static Word16 state_change_shift_r[2] = {STATE_1_TO_0_SHIFT_R, STATE_0_TO_1_SHIFT_R};
/* Energy scale table given 30,1 input scaling (also account for -6 dB shift on input) */
const static Word16 enrg_norm_shift[2] = {(FRACTIONAL_BITS_0-1+2), (FRACTIONAL_BITS_1-1+2)};
/* Automatic variables */
Word32 Lenrg; /* scaled as 30,1 */
Word32 Ltne; /* scaled as 22,9 */
Word32 Ltce; /* scaled as 22,9 or 27,4 */
Word16 tne_db; /* scaled as 7,8 */
Word16 tce_db; /* scaled as 7,8 */
Word16 input_buffer[FRM_LEN]; /* used for block normalising input data */
Word16 data_buffer[FFT_LEN]; /* used for in-place FFT */
Word16 ch_snr[NUM_CHAN]; /* scaled as 7,8 */
Word16 ch_snrq; /* scaled as 15,0 (in 0.375 dB steps) */
Word16 vm_sum; /* scaled as 15,0 */
Word16 ch_enrg_dev; /* scaled as 7,8 */
Word32 Lpeak; /* maximum channel energy */
Word16 p2a_flag; /* flag to indicate spectral peak-to-average ratio > 10 dB */
Word16 ch_enrg_db[NUM_CHAN]; /* scaled as 7,8 */
Word16 ch_noise_db; /* scaled as 7,8 */
Word16 alpha; /* scaled as 0,15 */
Word16 one_m_alpha; /* scaled as 0,15 */
Word16 update_flag; /* set to indicate a background noise estimate update */
Word16 i, j, j1, j2; /* Scratch variables */
Word16 hi1, lo1;
Word32 Ltmp, Ltmp1, Ltmp2;
Word16 tmp;
Word16 normb_shift; /* block norm shift count */
Word16 ivad; /* intermediate VAD decision (return value) */
Word16 tsnrq; /* total signal-to-noise ratio (quantized 3 dB steps) scaled as 15,0 */
Word16 xt; /* instantaneous frame SNR in dB, scaled as 7,8 */
Word16 state_change;
/* Increment frame counter */
st->Lframe_cnt = L_add(st->Lframe_cnt, 1);
/* Block normalize the input */
normb_shift = block_norm(farray_ptr, input_buffer, FRM_LEN, FFT_HEADROOM);
/* Pre-emphasize the input data and store in the data buffer with the appropriate offset */
for (i = 0; i < DELAY; i++)
{
data_buffer[i] = 0; move16();
}
st->pre_emp_mem = shr_r(st->pre_emp_mem, sub(st->last_normb_shift, normb_shift));
st->last_normb_shift = normb_shift; move16();
data_buffer[DELAY] = add(input_buffer[0], mult(PRE_EMP_FAC, st->pre_emp_mem)); move16();
for (i = DELAY + 1, j = 1; i < DELAY + FRM_LEN; i++, j++)
{
data_buffer[i] = add(input_buffer[j], mult(PRE_EMP_FAC, input_buffer[j-1])); move16();
}
st->pre_emp_mem = input_buffer[FRM_LEN-1]; move16();
for (i = DELAY + FRM_LEN; i < FFT_LEN; i++)
{
data_buffer[i] = 0; move16();
}
/* Perform FFT on the data buffer */
r_fft(data_buffer);
/* Use normb_shift factor to determine the scaling of the energy estimates */
state_change = 0; move16();
test();
if (st->shift_state == 0)
{ test();
if (sub(normb_shift, -FFT_HEADROOM+2) <= 0)
{
state_change = 1; move16();
st->shift_state = 1; move16();
}
}
else
{ test();
if (sub(normb_shift, -FFT_HEADROOM+5) >= 0)
{
state_change = 1; move16();
st->shift_state = 0; move16();
}
}
/* Scale channel energy estimate */ test();
if (state_change)
{
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
st->Lch_enrg[i] = L_shr(st->Lch_enrg[i], state_change_shift_r[st->shift_state]); move32();
}
}
/* Estimate the energy in each channel */
test();
if (L_sub(st->Lframe_cnt, 1) == 0)
{
alpha = 32767; move16();
one_m_alpha = 0; move16();
}
else
{
alpha = CEE_SM_FAC; move16();
one_m_alpha = ONE_MINUS_CEE_SM_FAC; move16();
}
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
Lenrg = 0; move16();
j1 = ch_tbl[i][0]; move16();
j2 = ch_tbl[i][1]; move16();
for (j = j1; j <= j2; j++)
{
Lenrg = L_mac(Lenrg, data_buffer[2 * j], data_buffer[2 * j]);
Lenrg = L_mac(Lenrg, data_buffer[2 * j + 1], data_buffer[2 * j + 1]);
}
/* Denorm energy & scale 30,1 according to the state */
Lenrg = L_shr_r(Lenrg, sub(shl(normb_shift, 1), enrg_norm_shift[st->shift_state]));
/* integrate over time: e[i] = (1-alpha)*e[i] + alpha*enrg/num_bins_in_chan */
tmp = mult(alpha, ch_tbl_sh[i]);
L_Extract (Lenrg, &hi1, &lo1);
Ltmp = Mpy_32_16(hi1, lo1, tmp);
L_Extract (st->Lch_enrg[i], &hi1, &lo1);
st->Lch_enrg[i] = L_add(Ltmp, Mpy_32_16(hi1, lo1, one_m_alpha)); move32();
test();
if (L_sub(st->Lch_enrg[i], min_chan_enrg[st->shift_state]) < 0)
{
st->Lch_enrg[i] = min_chan_enrg[st->shift_state]; move32();
}
}
/* Compute the total channel energy estimate (Ltce) */
Ltce = 0; move16();
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
Ltce = L_add(Ltce, st->Lch_enrg[i]);
}
/* Calculate spectral peak-to-average ratio, set flag if p2a > 10 dB */
Lpeak = 0; move32();
for (i = LO_CHAN+2; i <= HI_CHAN; i++) /* Sine waves not valid for low frequencies */
{ test();
if (L_sub(st->Lch_enrg [i], Lpeak) > 0)
{
Lpeak = st->Lch_enrg [i]; move32();
}
}
/* Set p2a_flag if peak (dB) > average channel energy (dB) + 10 dB */
/* Lpeak > Ltce/num_channels * 10^(10/10) */
/* Lpeak > (10/16)*Ltce */
L_Extract (Ltce, &hi1, &lo1);
Ltmp = Mpy_32_16(hi1, lo1, 20480);
test();
if (L_sub(Lpeak, Ltmp) > 0)
{
p2a_flag = TRUE; move16();
}
else
{
p2a_flag = FALSE; move16();
}
/* Initialize channel noise estimate to either the channel energy or fixed level */
/* Scale the energy appropriately to yield state 0 (22,9) scaling for noise */
test();
if (L_sub(st->Lframe_cnt, 4) <= 0)
{ test();
if (p2a_flag == TRUE)
{
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
st->Lch_noise[i] = INE_NOISE_0; move32();
}
}
else
{
for (i = LO_CHAN; i <= HI_CHAN; i++)
{ test();
if (L_sub(st->Lch_enrg[i], ine_noise[st->shift_state]) < 0)
{
st->Lch_noise[i] = INE_NOISE_0; move32();
}
else
{ test();
if (st->shift_state == 1)
{
st->Lch_noise[i] = L_shr(st->Lch_enrg[i], state_change_shift_r[0]);
move32();
}
else
{
st->Lch_noise[i] = st->Lch_enrg[i]; move32();
}
}
}
}
}
/* Compute the channel energy (in dB), the channel SNRs, and the sum of voice metrics */
vm_sum = 0; move16();
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
ch_enrg_db[i] = fn10Log10(st->Lch_enrg[i], fbits[st->shift_state]); move16();
ch_noise_db = fn10Log10(st->Lch_noise[i], FRACTIONAL_BITS_0);
ch_snr[i] = sub(ch_enrg_db[i], ch_noise_db); move16();
/* quantize channel SNR in 3/8 dB steps (scaled 7,8 => 15,0) */
/* ch_snr = round((snr/(3/8))>>8) */
/* = round(((0.6667*snr)<<2)>>8) */
/* = round((0.6667*snr)>>6) */
ch_snrq = shr_r(mult(21845, ch_snr[i]), 6);
/* Accumulate the sum of voice metrics */ test();
if (sub(ch_snrq, 89) < 0)
{ test();
if (ch_snrq > 0)
{
j = ch_snrq; move16();
}
else
{
j = 0; move16();
}
}
else
{
j = 89; move16();
}
vm_sum = add(vm_sum, vm_tbl[j]);
}
/* Initialize NOMINAL peak voice energy and average noise energy, calculate instantaneous SNR */
test(),test(),logic16();
if (L_sub(st->Lframe_cnt, 4) <= 0 || st->fupdate_flag == TRUE)
{
/* tce_db = (96 - 22 - 10*log10(64) (due to FFT)) scaled as 7,8 */
tce_db = 14320; move16();
st->negSNRvar = 0; move16();
st->negSNRbias = 0; move16();
/* Compute the total noise estimate (Ltne) */
Ltne = 0; move32();
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
Ltne = L_add(Ltne, st->Lch_noise[i]);
}
/* Get total noise in dB */
tne_db = fn10Log10(Ltne, FRACTIONAL_BITS_0);
/* Initialise instantaneous and long-term peak signal-to-noise ratios */
xt = sub(tce_db, tne_db);
st->tsnr = xt; move16();
}
else
{
/* Calculate instantaneous frame signal-to-noise ratio */
/* xt = 10*log10( sum(2.^(ch_snr*0.1*log2(10)))/length(ch_snr) ) */
Ltmp1 = 0; move32();
for (i=LO_CHAN; i<=HI_CHAN; i++) {
/* Ltmp2 = ch_snr[i] * 0.1 * log2(10); (ch_snr scaled as 7,8) */
Ltmp2 = L_shr(L_mult(ch_snr[i], 10885), 8);
L_Extract(Ltmp2, &hi1, &lo1);
hi1 = add(hi1, 3); /* 2^3 to compensate for negative SNR */
Ltmp1 = L_add(Ltmp1, Pow2(hi1, lo1));
}
xt = fn10Log10(Ltmp1, 4+3); /* average by 16, inverse compensation 2^3 */
/* Estimate long-term "peak" SNR */ test(),test();
if (sub(xt, st->tsnr) > 0)
{
/* tsnr = 0.9*tsnr + 0.1*xt; */
st->tsnr = round(L_add(L_mult(29491, st->tsnr), L_mult(3277, xt)));
}
/* else if (xt > 0.625*tsnr) */
else if (sub(xt, mult(20480, st->tsnr)) > 0)
{
/* tsnr = 0.998*tsnr + 0.002*xt; */
st->tsnr = round(L_add(L_mult(32702, st->tsnr), L_mult(66, xt)));
}
}
/* Quantize the long-term SNR in 3 dB steps, limit to 0 <= tsnrq <= 19 */
tsnrq = shr(mult(st->tsnr, 10923), 8);
/* tsnrq = min(19, max(0, tsnrq)); */ test(),test();
if (sub(tsnrq, 19) > 0)
{
tsnrq = 19; move16();
}
else if (tsnrq < 0)
{
tsnrq = 0; move16();
}
/* Calculate the negative SNR sensitivity bias */
test();
if (xt < 0)
{
/* negSNRvar = 0.99*negSNRvar + 0.01*xt*xt; */
/* xt scaled as 7,8 => xt*xt scaled as 14,17, shift to 7,8 and round */
tmp = round(L_shl(L_mult(xt, xt), 7));
st->negSNRvar = round(L_add(L_mult(32440, st->negSNRvar), L_mult(328, tmp)));
/* if (negSNRvar > 4.0) negSNRvar = 4.0; */ test();
if (sub(st->negSNRvar, 1024) > 0)
{
st->negSNRvar = 1024; move16();
}
/* negSNRbias = max(12.0*(negSNRvar - 0.65), 0.0); */
tmp = mult_r(shl(sub(st->negSNRvar, 166), 4), 24576); test();
if (tmp < 0)
{
st->negSNRbias = 0; move16();
}
else
{
st->negSNRbias = shr(tmp, 8);
}
}
/* Determine VAD as a function of the voice metric sum and quantized SNR */
tmp = add(vm_threshold_table[tsnrq], st->negSNRbias); test();
if (sub(vm_sum, tmp) > 0)
{
ivad = 1; move16();
st->burstcount = add(st->burstcount, 1); test();
if (sub(st->burstcount, burstcount_table[tsnrq]) > 0)
{
st->hangover = hangover_table[tsnrq]; move16();
}
}
else
{
st->burstcount = 0; move16();
st->hangover = sub(st->hangover, 1); test();
if (st->hangover <= 0)
{
ivad = 0; move16();
st->hangover = 0; move16();
}
else
{
ivad = 1; move16();
}
}
/* Calculate log spectral deviation */
ch_enrg_dev = 0; move16();
test();
if (L_sub(st->Lframe_cnt, 1) == 0)
{
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
st->ch_enrg_long_db[i] = ch_enrg_db[i]; move16();
}
}
else
{
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
tmp = abs_s(sub(st->ch_enrg_long_db[i], ch_enrg_db[i]));
ch_enrg_dev = add(ch_enrg_dev, tmp);
}
}
/*
* Calculate long term integration constant as a function of instantaneous SNR
* (i.e., high SNR (tsnr dB) -> slower integration (alpha = HIGH_ALPHA),
* low SNR (0 dB) -> faster integration (alpha = LOW_ALPHA)
*/
/* alpha = HIGH_ALPHA - ALPHA_RANGE * (tsnr - xt) / tsnr, low <= alpha <= high */
tmp = sub(st->tsnr, xt); test(),logic16(),test(),test();
if (tmp <= 0 || st->tsnr <= 0)
{
alpha = HIGH_ALPHA; move16();
one_m_alpha = 32768L-HIGH_ALPHA; move16();
}
else if (sub(tmp, st->tsnr) > 0)
{
alpha = LOW_ALPHA; move16();
one_m_alpha = 32768L-LOW_ALPHA; move16();
}
else
{
tmp = div_s(tmp, st->tsnr);
alpha = sub(HIGH_ALPHA, mult(ALPHA_RANGE, tmp));
one_m_alpha = sub(32767, alpha);
}
/* Calc long term log spectral energy */
for (i = LO_CHAN; i <= HI_CHAN; i++)
{
Ltmp1 = L_mult(one_m_alpha, ch_enrg_db[i]);
Ltmp2 = L_mult(alpha, st->ch_enrg_long_db[i]);
st->ch_enrg_long_db[i] = round(L_add(Ltmp1, Ltmp2));
}
/* Set or clear the noise update flags */
update_flag = FALSE; move16();
st->fupdate_flag = FALSE; move16();
test(),test();
if (sub(vm_sum, UPDATE_THLD) <= 0)
{ test();
if (st->burstcount == 0)
{
update_flag = TRUE; move16();
st->update_cnt = 0; move16();
}
}
else if (L_sub(Ltce, noise_floor_chan[st->shift_state]) > 0)
{ test();
if (sub(ch_enrg_dev, DEV_THLD) < 0)
{ test();
if (p2a_flag == FALSE)
{ test();
if (st->LTP_flag == FALSE)
{
st->update_cnt = add(st->update_cnt, 1); test();
if (sub(st->update_cnt, UPDATE_CNT_THLD) >= 0)
{
update_flag = TRUE; move16();
st->fupdate_flag = TRUE; move16();
}
}
}
}
}
test();
if (sub(st->update_cnt, st->last_update_cnt) == 0)
{
st->hyster_cnt = add(st->hyster_cnt, 1);
}
else
{
st->hyster_cnt = 0; move16();
}
st->last_update_cnt = st->update_cnt; move16();
test();
if (sub(st->hyster_cnt, HYSTER_CNT_THLD) > 0)
{
st->update_cnt = 0; move16();
}
/* Conditionally update the channel noise estimates */
test();
if (update_flag == TRUE)
{
/* Check shift state */ test();
if (st->shift_state == 1)
{
/* get factor to shift ch_enrg[] from state 1 to 0 (noise always state 0) */
tmp = state_change_shift_r[0]; move16();
}
else
{
/* No shift if already state 0 */
tmp = 0; move16();
}
/* Update noise energy estimate */
for (i = LO_CHAN; i <= HI_CHAN; i++)
{ test();
/* integrate over time: en[i] = (1-alpha)*en[i] + alpha*e[n] */
/* (extract with shift compensation for state 1) */
L_Extract (L_shr(st->Lch_enrg[i], tmp), &hi1, &lo1);
Ltmp = Mpy_32_16(hi1, lo1, CNE_SM_FAC);
L_Extract (st->Lch_noise[i], &hi1, &lo1);
st->Lch_noise[i] = L_add(Ltmp, Mpy_32_16(hi1, lo1, ONE_MINUS_CNE_SM_FAC)); move32();
/* Limit low level noise */ test();
if (L_sub(st->Lch_noise[i], MIN_NOISE_ENRG_0) < 0)
{
st->Lch_noise[i] = MIN_NOISE_ENRG_0; move32();
}
}
}
return(ivad);
} /* end of vad2 () */
/*-----------------------------------------------------------*
* procedure Calc_exc_rand *
* ~~~~~~~~~~~~~ *
* Computes comfort noise excitation *
* for SID and not-transmitted frames *
*-----------------------------------------------------------*/
void WebRtcG729fix_Calc_exc_rand(
int32_t L_exc_err[],
int16_t cur_gain, /* (i) : target sample gain */
int16_t *exc, /* (i/o) : excitation array */
int16_t *seed, /* (i) : current Vad decision */
int flag_cod /* (i) : encoder/decoder flag */
)
{
int16_t i, j, i_subfr;
int16_t temp1, temp2;
int16_t pos[4];
int16_t sign[4];
int16_t t0, frac;
int16_t *cur_exc;
int16_t g, Gp, Gp2;
int16_t excg[L_SUBFR], excs[L_SUBFR];
int32_t L_acc, L_ener, L_k;
int16_t max, hi, lo, inter_exc;
int16_t sh;
int16_t x1, x2;
if (cur_gain == 0) {
WebRtcSpl_ZerosArrayW16(exc, L_FRAME);
Gp = 0;
t0 = WebRtcSpl_AddSatW16(L_SUBFR,1);
for (i_subfr = 0; i_subfr < L_FRAME; i_subfr += L_SUBFR) {
if (flag_cod != FLAG_DEC)
WebRtcG729fix_update_exc_err(L_exc_err, Gp, t0);
}
return;
}
/* Loop on subframes */
cur_exc = exc;
for (i_subfr = 0; i_subfr < L_FRAME; i_subfr += L_SUBFR) {
/* generate random adaptive codebook & fixed codebook parameters */
/*****************************************************************/
temp1 = WebRtcG729fix_Random(seed);
frac = WebRtcSpl_SubSatW16((temp1 & (int16_t)0x0003), 1);
if(frac == 2) frac = 0;
temp1 = shr(temp1, 2);
t0 = WebRtcSpl_AddSatW16((temp1 & (int16_t)0x003F), 40);
temp1 = shr(temp1, 6);
temp2 = temp1 & (int16_t)0x0007;
pos[0] = WebRtcSpl_AddSatW16(shl(temp2, 2), temp2); /* 5 * temp2 */
temp1 = shr(temp1, 3);
sign[0] = temp1 & (int16_t)0x0001;
temp1 = shr(temp1, 1);
temp2 = temp1 & (int16_t)0x0007;
temp2 = WebRtcSpl_AddSatW16(shl(temp2, 2), temp2);
pos[1] = WebRtcSpl_AddSatW16(temp2, 1); /* 5 * x + 1 */
temp1 = shr(temp1, 3);
sign[1] = temp1 & (int16_t)0x0001;
temp1 = WebRtcG729fix_Random(seed);
temp2 = temp1 & (int16_t)0x0007;
temp2 = WebRtcSpl_AddSatW16(shl(temp2, 2), temp2);
pos[2] = WebRtcSpl_AddSatW16(temp2, 2); /* 5 * x + 2 */
temp1 = shr(temp1, 3);
sign[2] = temp1 & (int16_t)0x0001;
temp1 = shr(temp1, 1);
temp2 = temp1 & (int16_t)0x000F;
pos[3] = WebRtcSpl_AddSatW16((temp2 & (int16_t)1), 3); /* j+3*/
temp2 = (shr(temp2, 1)) & (int16_t)7;
temp2 = WebRtcSpl_AddSatW16(shl(temp2, 2), temp2); /* 5i */
pos[3] = WebRtcSpl_AddSatW16(pos[3], temp2);
temp1 = shr(temp1, 4);
sign[3] = temp1 & (int16_t)0x0001;
Gp = WebRtcG729fix_Random(seed) & (int16_t)0x1FFF; /* < 0.5 Q14 */
Gp2 = shl(Gp, 1); /* Q15 */
/* Generate gaussian excitation */
/********************************/
L_acc = 0L;
for(i=0; i<L_SUBFR; i++) {
temp1 = Gauss(seed);
L_acc = L_mac(L_acc, temp1, temp1);
excg[i] = temp1;
}
/*
Compute fact = alpha x cur_gain * sqrt(L_SUBFR / Eg)
with Eg = SUM(i=0->39) excg[i]^2
and alpha = 0.5
alpha x sqrt(L_SUBFR)/2 = 1 + FRAC1
*/
L_acc = WebRtcG729fix_Inv_sqrt(L_shr(L_acc,1)); /* Q30 */
WebRtcG729fix_L_Extract(L_acc, &hi, &lo);
/* cur_gain = cur_gainR << 3 */
temp1 = mult_r(cur_gain, FRAC1);
temp1 = WebRtcSpl_AddSatW16(cur_gain, temp1);
/* <=> alpha x cur_gainR x 2^2 x sqrt(L_SUBFR) */
L_acc = WebRtcG729fix_Mpy_32_16(hi, lo, temp1); /* fact << 17 */
sh = WebRtcSpl_NormW32(L_acc);
temp1 = extract_h(L_shl(L_acc, sh)); /* fact << (sh+1) */
sh = WebRtcSpl_SubSatW16(sh, 14);
for (i = 0; i < L_SUBFR; i++) {
temp2 = mult_r(excg[i], temp1);
temp2 = shr_r(temp2, sh); /* shl if sh < 0 */
excg[i] = temp2;
}
/* generate random adaptive excitation */
/****************************************/
WebRtcG729fix_Pred_lt_3(cur_exc, t0, frac, L_SUBFR);
/* compute adaptive + gaussian exc -> cur_exc */
/**********************************************/
max = 0;
for(i = 0; i < L_SUBFR; i++) {
temp1 = mult_r(cur_exc[i], Gp2);
temp1 = WebRtcSpl_AddSatW16(temp1, excg[i]); /* may overflow */
cur_exc[i] = temp1;
temp1 = abs_s(temp1);
if (temp1 > max)
max = temp1;
}
/* rescale cur_exc -> excs */
if (max == 0)
sh = 0;
else {
sh = WebRtcSpl_SubSatW16(3, WebRtcSpl_NormW16(max));
if (sh <= 0)
sh = 0;
}
for (i = 0; i < L_SUBFR; i++) {
excs[i] = shr(cur_exc[i], sh);
}
/* Compute fixed code gain */
/***************************/
/**********************************************************/
/*** Solve EQ(X) = 4 X**2 + 2 b X + c */
/**********************************************************/
L_ener = 0L;
for (i = 0; i < L_SUBFR; i++) {
L_ener = L_mac(L_ener, excs[i], excs[i]);
} /* ener x 2^(-2sh + 1) */
/* inter_exc = b >> sh */
inter_exc = 0;
for (i = 0; i < 4; i++) {
j = pos[i];
if (sign[i] == 0) {
inter_exc = WebRtcSpl_SubSatW16(inter_exc, excs[j]);
}
else {
inter_exc = WebRtcSpl_AddSatW16(inter_exc, excs[j]);
}
}
/* Compute k = cur_gainR x cur_gainR x L_SUBFR */
L_acc = L_mult(cur_gain, L_SUBFR);
L_acc = L_shr(L_acc, 6);
temp1 = extract_l(L_acc); /* cur_gainR x L_SUBFR x 2^(-2) */
L_k = L_mult(cur_gain, temp1); /* k << 2 */
temp1 = WebRtcSpl_AddSatW16(1, shl(sh,1));
L_acc = L_shr(L_k, temp1); /* k x 2^(-2sh+1) */
/* Compute delta = b^2 - 4 c */
L_acc = WebRtcSpl_SubSatW32(L_acc, L_ener); /* - 4 c x 2^(-2sh-1) */
inter_exc = shr(inter_exc, 1);
L_acc = L_mac(L_acc, inter_exc, inter_exc); /* 2^(-2sh-1) */
sh = WebRtcSpl_AddSatW16(sh, 1);
/* inter_exc = b x 2^(-sh) */
/* L_acc = delta x 2^(-2sh+1) */
if (L_acc < 0) {
/* adaptive excitation = 0 */
WEBRTC_SPL_MEMCPY_W16(cur_exc, excg, L_SUBFR);
temp1 = abs_s(excg[(int)pos[0]]) | abs_s(excg[(int)pos[1]]);
temp2 = abs_s(excg[(int)pos[2]]) | abs_s(excg[(int)pos[3]]);
temp1 = temp1 | temp2;
sh = ((temp1 & (int16_t)0x4000) == 0) ? (int16_t)1 : (int16_t)2;
inter_exc = 0;
for(i=0; i<4; i++) {
temp1 = shr(excg[(int)pos[i]], sh);
if(sign[i] == 0) {
inter_exc = WebRtcSpl_SubSatW16(inter_exc, temp1);
}
else {
inter_exc = WebRtcSpl_AddSatW16(inter_exc, temp1);
}
} /* inter_exc = b >> sh */
WebRtcG729fix_L_Extract(L_k, &hi, &lo);
L_acc = WebRtcG729fix_Mpy_32_16(hi, lo, K0); /* k x (1- alpha^2) << 2 */
temp1 = WebRtcSpl_SubSatW16(shl(sh, 1), 1); /* temp1 > 0 */
L_acc = L_shr(L_acc, temp1); /* 4k x (1 - alpha^2) << (-2sh+1) */
L_acc = L_mac(L_acc, inter_exc, inter_exc); /* delta << (-2sh+1) */
Gp = 0;
}
temp2 = Sqrt(L_acc); /* >> sh */
x1 = WebRtcSpl_SubSatW16(temp2, inter_exc);
x2 = negate(WebRtcSpl_AddSatW16(inter_exc, temp2)); /* x 2^(-sh+2) */
if(abs_s(x2) < abs_s(x1)) x1 = x2;
temp1 = WebRtcSpl_SubSatW16(2, sh);
g = shr_r(x1, temp1); /* shl if temp1 < 0 */
if (g >= 0) {
if (g > G_MAX)
g = G_MAX;
}
else {
if (WebRtcSpl_AddSatW16(g, G_MAX) < 0)
g = negate(G_MAX);
}
/* Update cur_exc with ACELP excitation */
for (i = 0; i < 4; i++) {
j = pos[i];
if (sign[i] != 0) {
cur_exc[j] = WebRtcSpl_AddSatW16(cur_exc[j], g);
}
else {
cur_exc[j] = WebRtcSpl_SubSatW16(cur_exc[j], g);
}
}
if (flag_cod != FLAG_DEC)
WebRtcG729fix_update_exc_err(L_exc_err, Gp, t0);
cur_exc += L_SUBFR;
} /* end of loop on subframes */
return;
}