vad2.c

arm音频编解码库

			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 () */


/**** Other related functions *****/

/*************************************************************************
*
*  Function:   vad2_init
*  Purpose:    Allocates state memory and initializes state memory
*
**************************************************************************
*/
int vad2_init (vadState2 **state)
{
    vadState2* s;
    
    if (state == (vadState2 **) NULL){
        fprintf(stderr, "vad2_init: invalid parameter\n");
        return -1;
    }
    *state = NULL;
    
    /* allocate memory */
    if ((s = (vadState2 *) malloc(sizeof(vadState2))) == NULL){
        fprintf(stderr, "vad2_init: can not malloc state structure\n");
        return -1;
    }
    
    vad2_reset(s);
    
    *state = s;
    
    return 0;
}

/***************************************************************************
 *
 *   FUNCTION NAME: vad2_reset()
 *
 *   PURPOSE:
 *     The purpose of this function is to initialise the vad2() state
 *     variables.
 *
 *   INPUTS:
 *
 *     &st
 *                     pointer to data structure of vad2 state variables
 *
 *   OUTPUTS:
 *
 *     none
 *
 *   RETURN VALUE:
 *
 *     none
 *
 *   DESCRIPTION:
 *
 *                     Set all values in vad2 state to zero.  Since it is
 *                     known that all elements in the structure contain
 *                     16 and 32 bit fixed point elements, the initialisation
 *                     is performed by zeroing out the number of bytes in the
 *                     structure divided by two.
 *
 *************************************************************************/

int vad2_reset (vadState2 * st)
{
	Word16	i;
	Word16	*ptr;

	if (st == (vadState2 *) NULL){
		fprintf(stderr, "vad2_reset: invalid parameter\n");
		return -1;
	}
	ptr = (Word16 *)st;				move16();

	for (i = 0; i < sizeof(vadState2)/2; i++)
	{
		*ptr++ = 0;				move16();
	}

	return 0;
}						/* end of vad2_reset () */

/*************************************************************************
*
*  Function:   vad2_exit
*  Purpose:    The memory used for state memory is freed
*
**************************************************************************
*/
void vad2_exit (vadState2 **state)
{
    if (state == NULL || *state == NULL)
        return;
    
    /* deallocate memory */
    free(*state);
    *state = NULL;
    
    return;
}