xenia-project/FFmpeg
1
0
Fork 0
mirror of https://github.com/xenia-project/FFmpeg.git synced 2024-12-12 05:35:56 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity
b82579a6ec
FFmpeg/libavcodec/aacpsy.c
Nathan Caldwell d56920e206 aacenc: Correct spreading calculation for high spreading. 
The 3GPP spec uses the following calculation for high spreading:

thr'_spr = max(thr_scaled, s_h(n) * thr_scaled(n-1))

where, n is defined as the current band, and s_h() is defined as "[...] the
distance of adjacent bands in Bark and a constant slope that is 15 dB/Bark
[...]". This is a little ambiguous as you would assume you want the Bark
width of the previous band for this calculation. However, this assumption
appears to be incorrect, and you really want the Bark width of the current
band. Coincidentally this is exactly what the spec calls for! =P

This noticeably improves Tom's Diner at low bitrates (I tested at 64kbps,
with mid/side disabled).

Patch by: Nathan Caldwell <saintdev@gmail.com>

Originally committed as revision 25622 to svn://svn.ffmpeg.org/ffmpeg/trunk
2010-11-01 07:45:13 +00:00

627 lines
22 KiB
C
Raw Blame History

/*
* AAC encoder psychoacoustic model
* Copyright (C) 2008 Konstantin Shishkov
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg 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
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file
* AAC encoder psychoacoustic model
*/
#include "avcodec.h"
#include "aactab.h"
#include "psymodel.h"
/***********************************
* TODOs:
* thresholds linearization after their modifications for attaining given bitrate
* try other bitrate controlling mechanism (maybe use ratecontrol.c?)
* control quality for quality-based output
**********************************/
/**
* constants for 3GPP AAC psychoacoustic model
* @{
*/
#define PSY_3GPP_SPREAD_HI 1.5f // spreading factor for ascending threshold spreading (15 dB/Bark)
#define PSY_3GPP_SPREAD_LOW 3.0f // spreading factor for descending threshold spreading (30 dB/Bark)
#define PSY_3GPP_RPEMIN 0.01f
#define PSY_3GPP_RPELEV 2.0f
/* LAME psy model constants */
#define PSY_LAME_FIR_LEN 21 ///< LAME psy model FIR order
#define AAC_BLOCK_SIZE_LONG 1024 ///< long block size
#define AAC_BLOCK_SIZE_SHORT 128 ///< short block size
#define AAC_NUM_BLOCKS_SHORT 8 ///< number of blocks in a short sequence
#define PSY_LAME_NUM_SUBBLOCKS 3 ///< Number of sub-blocks in each short block
/**
* @}
*/
/**
* information for single band used by 3GPP TS26.403-inspired psychoacoustic model
*/
typedef struct AacPsyBand{
float energy; ///< band energy
float ffac; ///< form factor
float thr; ///< energy threshold
float min_snr; ///< minimal SNR
float thr_quiet; ///< threshold in quiet
}AacPsyBand;
/**
* single/pair channel context for psychoacoustic model
*/
typedef struct AacPsyChannel{
AacPsyBand band[128]; ///< bands information
AacPsyBand prev_band[128]; ///< bands information from the previous frame
float win_energy; ///< sliding average of channel energy
float iir_state[2]; ///< hi-pass IIR filter state
uint8_t next_grouping; ///< stored grouping scheme for the next frame (in case of 8 short window sequence)
enum WindowSequence next_window_seq; ///< window sequence to be used in the next frame
/* LAME psy model specific members */
float attack_threshold; ///< attack threshold for this channel
float prev_energy_subshort[AAC_NUM_BLOCKS_SHORT * PSY_LAME_NUM_SUBBLOCKS];
int prev_attack; ///< attack value for the last short block in the previous sequence
}AacPsyChannel;
/**
* psychoacoustic model frame type-dependent coefficients
*/
typedef struct AacPsyCoeffs{
float ath [64]; ///< absolute threshold of hearing per bands
float barks [64]; ///< Bark value for each spectral band in long frame
float spread_low[64]; ///< spreading factor for low-to-high threshold spreading in long frame
float spread_hi [64]; ///< spreading factor for high-to-low threshold spreading in long frame
}AacPsyCoeffs;
/**
* 3GPP TS26.403-inspired psychoacoustic model specific data
*/
typedef struct AacPsyContext{
AacPsyCoeffs psy_coef[2];
AacPsyChannel *ch;
}AacPsyContext;
/**
* LAME psy model preset struct
*/
typedef struct {
int quality; ///< Quality to map the rest of the vaules to.
/* This is overloaded to be both kbps per channel in ABR mode, and
* requested quality in constant quality mode.
*/
float st_lrm; ///< short threshold for L, R, and M channels
} PsyLamePreset;
/**
* LAME psy model preset table for ABR
*/
static const PsyLamePreset psy_abr_map[] = {
/* TODO: Tuning. These were taken from LAME. */
/* kbps/ch st_lrm */
{ 8, 6.60},
{ 16, 6.60},
{ 24, 6.60},
{ 32, 6.60},
{ 40, 6.60},
{ 48, 6.60},
{ 56, 6.60},
{ 64, 6.40},
{ 80, 6.00},
{ 96, 5.60},
{112, 5.20},
{128, 5.20},
{160, 5.20}
};
/**
* LAME psy model preset table for constant quality
*/
static const PsyLamePreset psy_vbr_map[] = {
/* vbr_q st_lrm */
{ 0, 4.20},
{ 1, 4.20},
{ 2, 4.20},
{ 3, 4.20},
{ 4, 4.20},
{ 5, 4.20},
{ 6, 4.20},
{ 7, 4.20},
{ 8, 4.20},
{ 9, 4.20},
{10, 4.20}
};
/**
* LAME psy model FIR coefficient table
*/
static const float psy_fir_coeffs[] = {
-8.65163e-18 * 2, -0.00851586 * 2, -6.74764e-18 * 2, 0.0209036 * 2,
-3.36639e-17 * 2, -0.0438162 * 2, -1.54175e-17 * 2, 0.0931738 * 2,
-5.52212e-17 * 2, -0.313819 * 2
};
/**
* calculates the attack threshold for ABR from the above table for the LAME psy model
*/
static float lame_calc_attack_threshold(int bitrate)
{
/* Assume max bitrate to start with */
int lower_range = 12, upper_range = 12;
int lower_range_kbps = psy_abr_map[12].quality;
int upper_range_kbps = psy_abr_map[12].quality;
int i;
/* Determine which bitrates the value specified falls between.
* If the loop ends without breaking our above assumption of 320kbps was correct.
*/
for (i = 1; i < 13; i++) {
if (FFMAX(bitrate, psy_abr_map[i].quality) != bitrate) {
upper_range = i;
upper_range_kbps = psy_abr_map[i ].quality;
lower_range = i - 1;
lower_range_kbps = psy_abr_map[i - 1].quality;
break; /* Upper range found */
}
}
/* Determine which range the value specified is closer to */
if ((upper_range_kbps - bitrate) > (bitrate - lower_range_kbps))
return psy_abr_map[lower_range].st_lrm;
return psy_abr_map[upper_range].st_lrm;
}
/**
* LAME psy model specific initialization
*/
static void lame_window_init(AacPsyContext *ctx, AVCodecContext *avctx) {
int i, j;
for (i = 0; i < avctx->channels; i++) {
AacPsyChannel *pch = &ctx->ch[i];
if (avctx->flags & CODEC_FLAG_QSCALE)
pch->attack_threshold = psy_vbr_map[avctx->global_quality / FF_QP2LAMBDA].st_lrm;
else
pch->attack_threshold = lame_calc_attack_threshold(avctx->bit_rate / avctx->channels / 1000);
for (j = 0; j < AAC_NUM_BLOCKS_SHORT * PSY_LAME_NUM_SUBBLOCKS; j++)
pch->prev_energy_subshort[j] = 10.0f;
}
}
/**
* Calculate Bark value for given line.
*/
static av_cold float calc_bark(float f)
{
return 13.3f * atanf(0.00076f * f) + 3.5f * atanf((f / 7500.0f) * (f / 7500.0f));
}
#define ATH_ADD 4
/**
* Calculate ATH value for given frequency.
* Borrowed from Lame.
*/
static av_cold float ath(float f, float add)
{
f /= 1000.0f;
return 3.64 * pow(f, -0.8)
- 6.8 * exp(-0.6 * (f - 3.4) * (f - 3.4))
+ 6.0 * exp(-0.15 * (f - 8.7) * (f - 8.7))
+ (0.6 + 0.04 * add) * 0.001 * f * f * f * f;
}
static av_cold int psy_3gpp_init(FFPsyContext *ctx) {
AacPsyContext *pctx;
float bark;
int i, j, g, start;
float prev, minscale, minath;
ctx->model_priv_data = av_mallocz(sizeof(AacPsyContext));
pctx = (AacPsyContext*) ctx->model_priv_data;
minath = ath(3410, ATH_ADD);
for (j = 0; j < 2; j++) {
AacPsyCoeffs *coeffs = &pctx->psy_coef[j];
float line_to_frequency = ctx->avctx->sample_rate / (j ? 256.f : 2048.0f);
i = 0;
prev = 0.0;
for (g = 0; g < ctx->num_bands[j]; g++) {
i += ctx->bands[j][g];
bark = calc_bark((i-1) * line_to_frequency);
coeffs->barks[g] = (bark + prev) / 2.0;
prev = bark;
}
for (g = 0; g < ctx->num_bands[j] - 1; g++) {
coeffs->spread_low[g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_LOW);
coeffs->spread_hi [g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_HI);
}
start = 0;
for (g = 0; g < ctx->num_bands[j]; g++) {
minscale = ath(start * line_to_frequency, ATH_ADD);
for (i = 1; i < ctx->bands[j][g]; i++)
minscale = FFMIN(minscale, ath((start + i) * line_to_frequency, ATH_ADD));
coeffs->ath[g] = minscale - minath;
start += ctx->bands[j][g];
}
}
pctx->ch = av_mallocz(sizeof(AacPsyChannel) * ctx->avctx->channels);
lame_window_init(pctx, ctx->avctx);
return 0;
}
/**
* IIR filter used in block switching decision
*/
static float iir_filter(int in, float state[2])
{
float ret;
ret = 0.7548f * (in - state[0]) + 0.5095f * state[1];
state[0] = in;
state[1] = ret;
return ret;
}
/**
* window grouping information stored as bits (0 - new group, 1 - group continues)
*/
static const uint8_t window_grouping[9] = {
0xB6, 0x6C, 0xD8, 0xB2, 0x66, 0xC6, 0x96, 0x36, 0x36
};
/**
* Tell encoder which window types to use.
* @see 3GPP TS26.403 5.4.1 "Blockswitching"
*/
static FFPsyWindowInfo psy_3gpp_window(FFPsyContext *ctx,
const int16_t *audio, const int16_t *la,
int channel, int prev_type)
{
int i, j;
int br = ctx->avctx->bit_rate / ctx->avctx->channels;
int attack_ratio = br <= 16000 ? 18 : 10;
AacPsyContext *pctx = (AacPsyContext*) ctx->model_priv_data;
AacPsyChannel *pch = &pctx->ch[channel];
uint8_t grouping = 0;
int next_type = pch->next_window_seq;
FFPsyWindowInfo wi;
memset(&wi, 0, sizeof(wi));
if (la) {
float s[8], v;
int switch_to_eight = 0;
float sum = 0.0, sum2 = 0.0;
int attack_n = 0;
int stay_short = 0;
for (i = 0; i < 8; i++) {
for (j = 0; j < 128; j++) {
v = iir_filter(la[(i*128+j)*ctx->avctx->channels], pch->iir_state);
sum += v*v;
}
s[i] = sum;
sum2 += sum;
}
for (i = 0; i < 8; i++) {
if (s[i] > pch->win_energy * attack_ratio) {
attack_n = i + 1;
switch_to_eight = 1;
break;
}
}
pch->win_energy = pch->win_energy*7/8 + sum2/64;
wi.window_type[1] = prev_type;
switch (prev_type) {
case ONLY_LONG_SEQUENCE:
wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : ONLY_LONG_SEQUENCE;
break;
case LONG_START_SEQUENCE:
wi.window_type[0] = EIGHT_SHORT_SEQUENCE;
grouping = pch->next_grouping;
next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
break;
case LONG_STOP_SEQUENCE:
wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE;
next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : ONLY_LONG_SEQUENCE;
break;
case EIGHT_SHORT_SEQUENCE:
stay_short = next_type == EIGHT_SHORT_SEQUENCE || switch_to_eight;
wi.window_type[0] = stay_short ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
grouping = next_type == EIGHT_SHORT_SEQUENCE ? pch->next_grouping : 0;
next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE;
break;
}
pch->next_grouping = window_grouping[attack_n];
pch->next_window_seq = next_type;
} else {
for (i = 0; i < 3; i++)
wi.window_type[i] = prev_type;
grouping = (prev_type == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0;
}
wi.window_shape = 1;
if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) {
wi.num_windows = 1;
wi.grouping[0] = 1;
} else {
int lastgrp = 0;
wi.num_windows = 8;
for (i = 0; i < 8; i++) {
if (!((grouping >> i) & 1))
lastgrp = i;
wi.grouping[lastgrp]++;
}
}
return wi;
}
/**
* Calculate band thresholds as suggested in 3GPP TS26.403
*/
static void psy_3gpp_analyze(FFPsyContext *ctx, int channel,
const float *coefs, const FFPsyWindowInfo *wi)
{
AacPsyContext *pctx = (AacPsyContext*) ctx->model_priv_data;
AacPsyChannel *pch = &pctx->ch[channel];
int start = 0;
int i, w, g;
const int num_bands = ctx->num_bands[wi->num_windows == 8];
const uint8_t* band_sizes = ctx->bands[wi->num_windows == 8];
AacPsyCoeffs *coeffs = &pctx->psy_coef[wi->num_windows == 8];
//calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation"
for (w = 0; w < wi->num_windows*16; w += 16) {
for (g = 0; g < num_bands; g++) {
AacPsyBand *band = &pch->band[w+g];
band->energy = 0.0f;
for (i = 0; i < band_sizes[g]; i++)
band->energy += coefs[start+i] * coefs[start+i];
band->thr = band->energy * 0.001258925f;
start += band_sizes[g];
ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].energy = band->energy;
}
}
//modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation"
for (w = 0; w < wi->num_windows*16; w += 16) {
AacPsyBand *band = &pch->band[w];
for (g = 1; g < num_bands; g++)
band[g].thr = FFMAX(band[g].thr, band[g-1].thr * coeffs->spread_hi [g]);
for (g = num_bands - 2; g >= 0; g--)
band[g].thr = FFMAX(band[g].thr, band[g+1].thr * coeffs->spread_low[g]);
for (g = 0; g < num_bands; g++) {
band[g].thr_quiet = band[g].thr = FFMAX(band[g].thr, coeffs->ath[g]);
if (!(wi->window_type[0] == LONG_STOP_SEQUENCE || (wi->window_type[1] == LONG_START_SEQUENCE && !w)))
band[g].thr = FFMAX(PSY_3GPP_RPEMIN*band[g].thr, FFMIN(band[g].thr,
PSY_3GPP_RPELEV*pch->prev_band[w+g].thr_quiet));
ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].threshold = band[g].thr;
}
}
memcpy(pch->prev_band, pch->band, sizeof(pch->band));
}
static av_cold void psy_3gpp_end(FFPsyContext *apc)
{
AacPsyContext *pctx = (AacPsyContext*) apc->model_priv_data;
av_freep(&pctx->ch);
av_freep(&apc->model_priv_data);
}
static void lame_apply_block_type(AacPsyChannel *ctx, FFPsyWindowInfo *wi, int uselongblock)
{
int blocktype = ONLY_LONG_SEQUENCE;
if (uselongblock) {
if (ctx->next_window_seq == EIGHT_SHORT_SEQUENCE)
blocktype = LONG_STOP_SEQUENCE;
} else {
blocktype = EIGHT_SHORT_SEQUENCE;
if (ctx->next_window_seq == ONLY_LONG_SEQUENCE)
ctx->next_window_seq = LONG_START_SEQUENCE;
if (ctx->next_window_seq == LONG_STOP_SEQUENCE)
ctx->next_window_seq = EIGHT_SHORT_SEQUENCE;
}
wi->window_type[0] = ctx->next_window_seq;
ctx->next_window_seq = blocktype;
}
static FFPsyWindowInfo psy_lame_window(FFPsyContext *ctx,
const int16_t *audio, const int16_t *la,
int channel, int prev_type)
{
AacPsyContext *pctx = (AacPsyContext*) ctx->model_priv_data;
AacPsyChannel *pch = &pctx->ch[channel];
int grouping = 0;
int uselongblock = 1;
int attacks[AAC_NUM_BLOCKS_SHORT + 1] = { 0 };
int i;
FFPsyWindowInfo wi;
memset(&wi, 0, sizeof(wi));
if (la) {
float hpfsmpl[AAC_BLOCK_SIZE_LONG];
float const *pf = hpfsmpl;
float attack_intensity[(AAC_NUM_BLOCKS_SHORT + 1) * PSY_LAME_NUM_SUBBLOCKS];
float energy_subshort[(AAC_NUM_BLOCKS_SHORT + 1) * PSY_LAME_NUM_SUBBLOCKS];
float energy_short[AAC_NUM_BLOCKS_SHORT + 1] = { 0 };
int chans = ctx->avctx->channels;
const int16_t *firbuf = la + (AAC_BLOCK_SIZE_SHORT/4 - PSY_LAME_FIR_LEN) * chans;
int j, att_sum = 0;
/* LAME comment: apply high pass filter of fs/4 */
for (i = 0; i < AAC_BLOCK_SIZE_LONG; i++) {
float sum1, sum2;
sum1 = firbuf[(i + ((PSY_LAME_FIR_LEN - 1) / 2)) * chans];
sum2 = 0.0;
for (j = 0; j < ((PSY_LAME_FIR_LEN - 1) / 2) - 1; j += 2) {
sum1 += psy_fir_coeffs[j] * (firbuf[(i + j) * chans] + firbuf[(i + PSY_LAME_FIR_LEN - j) * chans]);
sum2 += psy_fir_coeffs[j + 1] * (firbuf[(i + j + 1) * chans] + firbuf[(i + PSY_LAME_FIR_LEN - j - 1) * chans]);
}
hpfsmpl[i] = sum1 + sum2;
}
/* Calculate the energies of each sub-shortblock */
for (i = 0; i < PSY_LAME_NUM_SUBBLOCKS; i++) {
energy_subshort[i] = pch->prev_energy_subshort[i + ((AAC_NUM_BLOCKS_SHORT - 1) * PSY_LAME_NUM_SUBBLOCKS)];
assert(pch->prev_energy_subshort[i + ((AAC_NUM_BLOCKS_SHORT - 2) * PSY_LAME_NUM_SUBBLOCKS + 1)] > 0);
attack_intensity[i] = energy_subshort[i] / pch->prev_energy_subshort[i + ((AAC_NUM_BLOCKS_SHORT - 2) * PSY_LAME_NUM_SUBBLOCKS + 1)];
energy_short[0] += energy_subshort[i];
}
for (i = 0; i < AAC_NUM_BLOCKS_SHORT * PSY_LAME_NUM_SUBBLOCKS; i++) {
float const *const pfe = pf + AAC_BLOCK_SIZE_LONG / (AAC_NUM_BLOCKS_SHORT * PSY_LAME_NUM_SUBBLOCKS);
float p = 1.0f;
for (; pf < pfe; pf++)
if (p < fabsf(*pf))
p = fabsf(*pf);
pch->prev_energy_subshort[i] = energy_subshort[i + PSY_LAME_NUM_SUBBLOCKS] = p;
energy_short[1 + i / PSY_LAME_NUM_SUBBLOCKS] += p;
/* FIXME: The indexes below are [i + 3 - 2] in the LAME source.
* Obviously the 3 and 2 have some significance, or this would be just [i + 1]
* (which is what we use here). What the 3 stands for is ambigious, as it is both
* number of short blocks, and the number of sub-short blocks.
* It seems that LAME is comparing each sub-block to sub-block + 1 in the
* previous block.
*/
if (p > energy_subshort[i + 1])
p = p / energy_subshort[i + 1];
else if (energy_subshort[i + 1] > p * 10.0f)
p = energy_subshort[i + 1] / (p * 10.0f);
else
p = 0.0;
attack_intensity[i + PSY_LAME_NUM_SUBBLOCKS] = p;
}
/* compare energy between sub-short blocks */
for (i = 0; i < (AAC_NUM_BLOCKS_SHORT + 1) * PSY_LAME_NUM_SUBBLOCKS; i++)
if (!attacks[i / PSY_LAME_NUM_SUBBLOCKS])
if (attack_intensity[i] > pch->attack_threshold)
attacks[i / PSY_LAME_NUM_SUBBLOCKS] = (i % PSY_LAME_NUM_SUBBLOCKS) + 1;
/* should have energy change between short blocks, in order to avoid periodic signals */
/* Good samples to show the effect are Trumpet test songs */
/* GB: tuned (1) to avoid too many short blocks for test sample TRUMPET */
/* RH: tuned (2) to let enough short blocks through for test sample FSOL and SNAPS */
for (i = 1; i < AAC_NUM_BLOCKS_SHORT + 1; i++) {
float const u = energy_short[i - 1];
float const v = energy_short[i];
float const m = FFMAX(u, v);
if (m < 40000) { /* (2) */
if (u < 1.7f * v && v < 1.7f * u) { /* (1) */
if (i == 1 && attacks[0] < attacks[i])
attacks[0] = 0;
attacks[i] = 0;
}
}
att_sum += attacks[i];
}
if (attacks[0] <= pch->prev_attack)
attacks[0] = 0;
att_sum += attacks[0];
/* 3 below indicates the previous attack happened in the last sub-block of the previous sequence */
if (pch->prev_attack == 3 || att_sum) {
uselongblock = 0;
if (attacks[1] && attacks[0])
attacks[1] = 0;
if (attacks[2] && attacks[1])
attacks[2] = 0;
if (attacks[3] && attacks[2])
attacks[3] = 0;
if (attacks[4] && attacks[3])
attacks[4] = 0;
if (attacks[5] && attacks[4])
attacks[5] = 0;
if (attacks[6] && attacks[5])
attacks[6] = 0;
if (attacks[7] && attacks[6])
attacks[7] = 0;
if (attacks[8] && attacks[7])
attacks[8] = 0;
}
} else {
/* We have no lookahead info, so just use same type as the previous sequence. */
uselongblock = !(prev_type == EIGHT_SHORT_SEQUENCE);
}
lame_apply_block_type(pch, &wi, uselongblock);
wi.window_type[1] = prev_type;
if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) {
wi.num_windows = 1;
wi.grouping[0] = 1;
if (wi.window_type[0] == LONG_START_SEQUENCE)
wi.window_shape = 0;
else
wi.window_shape = 1;
} else {
int lastgrp = 0;
wi.num_windows = 8;
wi.window_shape = 0;
for (i = 0; i < 8; i++) {
if (!((pch->next_grouping >> i) & 1))
lastgrp = i;
wi.grouping[lastgrp]++;
}
}
/* Determine grouping, based on the location of the first attack, and save for
* the next frame.
* FIXME: Move this to analysis.
* TODO: Tune groupings depending on attack location
* TODO: Handle more than one attack in a group
*/
for (i = 0; i < 9; i++) {
if (attacks[i]) {
grouping = i;
break;
}
}
pch->next_grouping = window_grouping[grouping];
pch->prev_attack = attacks[8];
return wi;
}
const FFPsyModel ff_aac_psy_model =
{
.name = "3GPP TS 26.403-inspired model",
.init = psy_3gpp_init,
.window = psy_lame_window,
.analyze = psy_3gpp_analyze,
.end = psy_3gpp_end,
};
Reference in New Issue View Git Blame Copy Permalink