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327 lines
11 KiB
327 lines
11 KiB
/* |
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* AAC encoder psychoacoustic model |
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* Copyright (C) 2008 Konstantin Shishkov |
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* |
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* This file is part of FFmpeg. |
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* |
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* FFmpeg is free software; you can redistribute it and/or |
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* modify it under the terms of the GNU Lesser General Public |
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* License as published by the Free Software Foundation; either |
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* version 2.1 of the License, or (at your option) any later version. |
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* |
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* FFmpeg is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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* Lesser General Public License for more details. |
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* |
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* You should have received a copy of the GNU Lesser General Public |
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* License along with FFmpeg; if not, write to the Free Software |
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA |
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*/ |
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/** |
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* @file |
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* AAC encoder psychoacoustic model |
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*/ |
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#include "avcodec.h" |
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#include "aactab.h" |
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#include "psymodel.h" |
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/*********************************** |
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* TODOs: |
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* thresholds linearization after their modifications for attaining given bitrate |
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* try other bitrate controlling mechanism (maybe use ratecontrol.c?) |
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* control quality for quality-based output |
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**********************************/ |
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/** |
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* constants for 3GPP AAC psychoacoustic model |
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* @{ |
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*/ |
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#define PSY_3GPP_SPREAD_LOW 1.5f // spreading factor for ascending threshold spreading (15 dB/Bark) |
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#define PSY_3GPP_SPREAD_HI 3.0f // spreading factor for descending threshold spreading (30 dB/Bark) |
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#define PSY_3GPP_RPEMIN 0.01f |
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#define PSY_3GPP_RPELEV 2.0f |
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/** |
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* @} |
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*/ |
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/** |
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* information for single band used by 3GPP TS26.403-inspired psychoacoustic model |
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*/ |
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typedef struct Psy3gppBand{ |
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float energy; ///< band energy |
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float ffac; ///< form factor |
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float thr; ///< energy threshold |
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float min_snr; ///< minimal SNR |
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float thr_quiet; ///< threshold in quiet |
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}Psy3gppBand; |
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/** |
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* single/pair channel context for psychoacoustic model |
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*/ |
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typedef struct Psy3gppChannel{ |
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Psy3gppBand band[128]; ///< bands information |
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Psy3gppBand prev_band[128]; ///< bands information from the previous frame |
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float win_energy; ///< sliding average of channel energy |
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float iir_state[2]; ///< hi-pass IIR filter state |
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uint8_t next_grouping; ///< stored grouping scheme for the next frame (in case of 8 short window sequence) |
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enum WindowSequence next_window_seq; ///< window sequence to be used in the next frame |
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}Psy3gppChannel; |
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/** |
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* psychoacoustic model frame type-dependent coefficients |
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*/ |
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typedef struct Psy3gppCoeffs{ |
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float ath [64]; ///< absolute threshold of hearing per bands |
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float barks [64]; ///< Bark value for each spectral band in long frame |
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float spread_low[64]; ///< spreading factor for low-to-high threshold spreading in long frame |
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float spread_hi [64]; ///< spreading factor for high-to-low threshold spreading in long frame |
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}Psy3gppCoeffs; |
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/** |
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* 3GPP TS26.403-inspired psychoacoustic model specific data |
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*/ |
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typedef struct Psy3gppContext{ |
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Psy3gppCoeffs psy_coef[2]; |
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Psy3gppChannel *ch; |
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}Psy3gppContext; |
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/** |
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* Calculate Bark value for given line. |
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*/ |
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static av_cold float calc_bark(float f) |
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{ |
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return 13.3f * atanf(0.00076f * f) + 3.5f * atanf((f / 7500.0f) * (f / 7500.0f)); |
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} |
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#define ATH_ADD 4 |
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/** |
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* Calculate ATH value for given frequency. |
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* Borrowed from Lame. |
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*/ |
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static av_cold float ath(float f, float add) |
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{ |
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f /= 1000.0f; |
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return 3.64 * pow(f, -0.8) |
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- 6.8 * exp(-0.6 * (f - 3.4) * (f - 3.4)) |
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+ 6.0 * exp(-0.15 * (f - 8.7) * (f - 8.7)) |
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+ (0.6 + 0.04 * add) * 0.001 * f * f * f * f; |
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} |
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static av_cold int psy_3gpp_init(FFPsyContext *ctx) { |
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Psy3gppContext *pctx; |
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float barks[1024]; |
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int i, j, g, start; |
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float prev, minscale, minath; |
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ctx->model_priv_data = av_mallocz(sizeof(Psy3gppContext)); |
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pctx = (Psy3gppContext*) ctx->model_priv_data; |
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for (i = 0; i < 1024; i++) |
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barks[i] = calc_bark(i * ctx->avctx->sample_rate / 2048.0); |
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minath = ath(3410, ATH_ADD); |
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for (j = 0; j < 2; j++) { |
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Psy3gppCoeffs *coeffs = &pctx->psy_coef[j]; |
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i = 0; |
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prev = 0.0; |
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for (g = 0; g < ctx->num_bands[j]; g++) { |
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i += ctx->bands[j][g]; |
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coeffs->barks[g] = (barks[i - 1] + prev) / 2.0; |
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prev = barks[i - 1]; |
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} |
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for (g = 0; g < ctx->num_bands[j] - 1; g++) { |
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coeffs->spread_low[g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_LOW); |
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coeffs->spread_hi [g] = pow(10.0, -(coeffs->barks[g+1] - coeffs->barks[g]) * PSY_3GPP_SPREAD_HI); |
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} |
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start = 0; |
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for (g = 0; g < ctx->num_bands[j]; g++) { |
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minscale = ath(ctx->avctx->sample_rate * start / 1024.0, ATH_ADD); |
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for (i = 1; i < ctx->bands[j][g]; i++) |
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minscale = FFMIN(minscale, ath(ctx->avctx->sample_rate * (start + i) / 1024.0 / 2.0, ATH_ADD)); |
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coeffs->ath[g] = minscale - minath; |
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start += ctx->bands[j][g]; |
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} |
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} |
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pctx->ch = av_mallocz(sizeof(Psy3gppChannel) * ctx->avctx->channels); |
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return 0; |
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} |
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/** |
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* IIR filter used in block switching decision |
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*/ |
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static float iir_filter(int in, float state[2]) |
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{ |
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float ret; |
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ret = 0.7548f * (in - state[0]) + 0.5095f * state[1]; |
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state[0] = in; |
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state[1] = ret; |
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return ret; |
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} |
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/** |
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* window grouping information stored as bits (0 - new group, 1 - group continues) |
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*/ |
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static const uint8_t window_grouping[9] = { |
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0xB6, 0x6C, 0xD8, 0xB2, 0x66, 0xC6, 0x96, 0x36, 0x36 |
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}; |
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/** |
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* Tell encoder which window types to use. |
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* @see 3GPP TS26.403 5.4.1 "Blockswitching" |
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*/ |
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static FFPsyWindowInfo psy_3gpp_window(FFPsyContext *ctx, |
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const int16_t *audio, const int16_t *la, |
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int channel, int prev_type) |
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{ |
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int i, j; |
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int br = ctx->avctx->bit_rate / ctx->avctx->channels; |
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int attack_ratio = br <= 16000 ? 18 : 10; |
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Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data; |
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Psy3gppChannel *pch = &pctx->ch[channel]; |
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uint8_t grouping = 0; |
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int next_type = pch->next_window_seq; |
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FFPsyWindowInfo wi; |
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memset(&wi, 0, sizeof(wi)); |
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if (la) { |
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float s[8], v; |
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int switch_to_eight = 0; |
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float sum = 0.0, sum2 = 0.0; |
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int attack_n = 0; |
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int stay_short = 0; |
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for (i = 0; i < 8; i++) { |
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for (j = 0; j < 128; j++) { |
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v = iir_filter(la[(i*128+j)*ctx->avctx->channels], pch->iir_state); |
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sum += v*v; |
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} |
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s[i] = sum; |
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sum2 += sum; |
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} |
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for (i = 0; i < 8; i++) { |
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if (s[i] > pch->win_energy * attack_ratio) { |
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attack_n = i + 1; |
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switch_to_eight = 1; |
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break; |
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} |
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} |
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pch->win_energy = pch->win_energy*7/8 + sum2/64; |
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wi.window_type[1] = prev_type; |
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switch (prev_type) { |
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case ONLY_LONG_SEQUENCE: |
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wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE; |
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next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : ONLY_LONG_SEQUENCE; |
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break; |
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case LONG_START_SEQUENCE: |
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wi.window_type[0] = EIGHT_SHORT_SEQUENCE; |
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grouping = pch->next_grouping; |
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next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE; |
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break; |
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case LONG_STOP_SEQUENCE: |
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wi.window_type[0] = switch_to_eight ? LONG_START_SEQUENCE : ONLY_LONG_SEQUENCE; |
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next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : ONLY_LONG_SEQUENCE; |
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break; |
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case EIGHT_SHORT_SEQUENCE: |
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stay_short = next_type == EIGHT_SHORT_SEQUENCE || switch_to_eight; |
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wi.window_type[0] = stay_short ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE; |
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grouping = next_type == EIGHT_SHORT_SEQUENCE ? pch->next_grouping : 0; |
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next_type = switch_to_eight ? EIGHT_SHORT_SEQUENCE : LONG_STOP_SEQUENCE; |
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break; |
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} |
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pch->next_grouping = window_grouping[attack_n]; |
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pch->next_window_seq = next_type; |
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} else { |
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for (i = 0; i < 3; i++) |
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wi.window_type[i] = prev_type; |
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grouping = (prev_type == EIGHT_SHORT_SEQUENCE) ? window_grouping[0] : 0; |
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} |
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wi.window_shape = 1; |
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if (wi.window_type[0] != EIGHT_SHORT_SEQUENCE) { |
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wi.num_windows = 1; |
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wi.grouping[0] = 1; |
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} else { |
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int lastgrp = 0; |
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wi.num_windows = 8; |
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for (i = 0; i < 8; i++) { |
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if (!((grouping >> i) & 1)) |
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lastgrp = i; |
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wi.grouping[lastgrp]++; |
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} |
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} |
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return wi; |
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} |
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/** |
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* Calculate band thresholds as suggested in 3GPP TS26.403 |
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*/ |
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static void psy_3gpp_analyze(FFPsyContext *ctx, int channel, |
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const float *coefs, FFPsyWindowInfo *wi) |
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{ |
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Psy3gppContext *pctx = (Psy3gppContext*) ctx->model_priv_data; |
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Psy3gppChannel *pch = &pctx->ch[channel]; |
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int start = 0; |
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int i, w, g; |
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const int num_bands = ctx->num_bands[wi->num_windows == 8]; |
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const uint8_t* band_sizes = ctx->bands[wi->num_windows == 8]; |
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Psy3gppCoeffs *coeffs = &pctx->psy_coef[wi->num_windows == 8]; |
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//calculate energies, initial thresholds and related values - 5.4.2 "Threshold Calculation" |
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for (w = 0; w < wi->num_windows*16; w += 16) { |
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for (g = 0; g < num_bands; g++) { |
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Psy3gppBand *band = &pch->band[w+g]; |
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band->energy = 0.0f; |
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for (i = 0; i < band_sizes[g]; i++) |
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band->energy += coefs[start+i] * coefs[start+i]; |
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band->energy *= 1.0f / (512*512); |
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band->thr = band->energy * 0.001258925f; |
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start += band_sizes[g]; |
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ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].energy = band->energy; |
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} |
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} |
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//modify thresholds - spread, threshold in quiet - 5.4.3 "Spreaded Energy Calculation" |
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for (w = 0; w < wi->num_windows*16; w += 16) { |
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Psy3gppBand *band = &pch->band[w]; |
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for (g = 1; g < num_bands; g++) |
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band[g].thr = FFMAX(band[g].thr, band[g-1].thr * coeffs->spread_low[g-1]); |
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for (g = num_bands - 2; g >= 0; g--) |
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band[g].thr = FFMAX(band[g].thr, band[g+1].thr * coeffs->spread_hi [g]); |
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for (g = 0; g < num_bands; g++) { |
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band[g].thr_quiet = FFMAX(band[g].thr, coeffs->ath[g]); |
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if (wi->num_windows != 8 && wi->window_type[1] != EIGHT_SHORT_SEQUENCE) |
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band[g].thr_quiet = FFMAX(PSY_3GPP_RPEMIN*band[g].thr_quiet, |
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FFMIN(band[g].thr_quiet, |
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PSY_3GPP_RPELEV*pch->prev_band[w+g].thr_quiet)); |
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band[g].thr = FFMAX(band[g].thr, band[g].thr_quiet * 0.25); |
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ctx->psy_bands[channel*PSY_MAX_BANDS+w+g].threshold = band[g].thr; |
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} |
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} |
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memcpy(pch->prev_band, pch->band, sizeof(pch->band)); |
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} |
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static av_cold void psy_3gpp_end(FFPsyContext *apc) |
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{ |
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Psy3gppContext *pctx = (Psy3gppContext*) apc->model_priv_data; |
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av_freep(&pctx->ch); |
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av_freep(&apc->model_priv_data); |
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} |
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const FFPsyModel ff_aac_psy_model = |
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{ |
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.name = "3GPP TS 26.403-inspired model", |
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.init = psy_3gpp_init, |
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.window = psy_3gpp_window, |
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.analyze = psy_3gpp_analyze, |
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.end = psy_3gpp_end, |
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};
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