/external/webrtc/webrtc/modules/audio_processing/vad/ |
H A D | pitch_internal.h | 17 double* gains,
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H A D | pitch_internal.cc | 29 double* gains, 39 gains[n] = log(gains[n] + 1e-12); 41 // Interpolate lags and gains. 42 PitchInterpolation(*log_old_gain, gains, log_pitch_gain); 43 *log_old_gain = gains[num_in_frames - 1]; 28 GetSubframesPitchParameters(int sampling_rate_hz, double* gains, double* lags, int num_in_frames, int num_out_frames, double* log_old_gain, double* old_lag, double* log_pitch_gain, double* pitch_lag_hz) argument
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H A D | pitch_internal_unittest.cc | 23 double gains[] = {0.6, 0.2, 0.5, 0.4}; local 31 double expected_log_old_gain = log(gains[kNumInputParameters - 1]); 40 GetSubframesPitchParameters(kSamplingRateHz, gains, lags, kNumInputParameters,
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H A D | vad_audio_proc.cc | 229 // Using iSAC functions to estimate pitch gains & lags. 237 double gains[kNumPitchSubframes]; local 255 pitch_analysis_handle_.get(), lags, gains); 260 kSampleRateHz / 2, gains, lags, kNumPitchSubframes, kNum10msSubframes,
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/external/webrtc/webrtc/modules/audio_coding/codecs/isac/main/source/ |
H A D | pitch_estimator.h | 29 double *gains); 41 double *gains); 47 double *gains); 53 double *gains); 60 double *gains);
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H A D | pitch_filter.c | 101 * damper_state_dg : state of damping filter for different trial gains. 214 /* Update filter parameters based on the pitch-gains and pitch-lags. */ 240 * Filter a frame of 30 millisecond, given pitch-lags and pitch-gains. 245 * gains : pointer to pitch-gians, 4 gains per frame. 252 * pitch-gains. 261 double* lags, double* gains, PitchFilterOperation mode, 294 gains[n] *= -kEnhancer; 305 old_gain = gains[0]; 319 gain_delta = (gains[ 260 FilterFrame(const double* in_data, PitchFiltstr* filter_state, double* lags, double* gains, PitchFilterOperation mode, double* out_data, double out_dg[][PITCH_FRAME_LEN + QLOOKAHEAD]) argument 358 WebRtcIsac_PitchfilterPre(double* in_data, double* out_data, PitchFiltstr* pf_state, double* lags, double* gains) argument 364 WebRtcIsac_PitchfilterPre_la(double* in_data, double* out_data, PitchFiltstr* pf_state, double* lags, double* gains) argument 371 WebRtcIsac_PitchfilterPre_gains( double* in_data, double* out_data, double out_dg[][PITCH_FRAME_LEN + QLOOKAHEAD], PitchFiltstr *pf_state, double* lags, double* gains) argument 379 WebRtcIsac_PitchfilterPost(double* in_data, double* out_data, PitchFiltstr* pf_state, double* lags, double* gains) argument [all...] |
H A D | pitch_estimator.c | 472 double *gains) 515 /* Iterative optimization of gains */ 522 /* set initial gains */ 524 gains[k] = PITCH_MAX_GAIN_06; 528 /* compute Jacobian of pre-filter output towards gains */ 529 WebRtcIsac_PitchfilterPre_gains(Whitened, out_G, out_dG, &(State->PFstr_wght), lags, gains); 551 tmp += kWeight[k+1][m+1] * gains[m]; 562 tmp = 1.0 / (1 - gains[k]); 566 tmp = 1.0 / (1 - gains[3]); 600 /* update gains an 468 WebRtcIsac_PitchAnalysis(const double *in, double *out, PitchAnalysisStruct *State, double *lags, double *gains) argument [all...] |
/external/libopus/silk/float/ |
H A D | residual_energy_FLP.c | 95 const silk_float gains[], /* I Quantization gains */ 109 nrgs[ 0 ] = ( silk_float )( gains[ 0 ] * gains[ 0 ] * silk_energy_FLP( LPC_res_ptr + 0 * shift, subfr_length ) ); 110 nrgs[ 1 ] = ( silk_float )( gains[ 1 ] * gains[ 1 ] * silk_energy_FLP( LPC_res_ptr + 1 * shift, subfr_length ) ); 114 nrgs[ 2 ] = ( silk_float )( gains[ 2 ] * gains[ 2 ] * silk_energy_FLP( LPC_res_ptr + 0 * shift, subfr_length ) ); 115 nrgs[ 3 ] = ( silk_float )( gains[ 3 ] * gains[ 91 silk_residual_energy_FLP( silk_float nrgs[ MAX_NB_SUBFR ], const silk_float x[], silk_float a[ 2 ][ MAX_LPC_ORDER ], const silk_float gains[], const opus_int subfr_length, const opus_int nb_subfr, const opus_int LPC_order ) argument [all...] |
H A D | main_FLP.h | 158 const silk_float invGains[ MAX_NB_SUBFR ], /* I Inverse quantization gains */ 170 const silk_float gains[], /* I Quantization gains */ 187 silk_float B[ MAX_NB_SUBFR * LTP_ORDER ], /* O Quantized LTP gains */ 208 /* Processing of gains */
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/external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/ |
H A D | split_handler_ops_test.py | 46 partitions, gains, splits = ( 61 partitions, gains, splits = sess.run([partitions, gains, splits]) 86 expected_left_gain + expected_right_gain - expected_bias_gain, gains[0], 103 self.assertAllClose(0.0, gains[1], 0.00001) 119 partitions, gains, splits = ( 134 partitions, gains, splits = sess.run([partitions, gains, splits]) 158 partitions, gains, splits = ( 173 partitions, gains, split [all...] |
H A D | training_ops_test.py | 322 gains=[handler1_gains, handler2_gains, handler3_gains], 473 gains=[handler1_gains, handler2_gains, handler3_gains], 658 gains=[handler1_gains, handler2_gains, handler3_gains], 795 gains=[handler1_gains, handler2_gains], 866 gains=[handler1_gains, handler2_gains, handler3_gains], 968 gains=[handler1_gains, handler2_gains], 1049 gains=[handler1_gains], 1116 gains=[handler1_gains, handler2_gains], 1195 gains=[handler1_gains], 1365 gains [all...] |
/external/libopus/silk/fixed/ |
H A D | residual_energy_FIX.c | 42 const opus_int32 gains[ MAX_NB_SUBFR ], /* I Quantization gains */ 82 /* Apply the squared subframe gains */ 84 /* Fully upscale gains and energies */ 86 lz2 = silk_CLZ32( gains[ i ] ) - 1; 88 tmp32 = silk_LSHIFT32( gains[ i ], lz2 ); 90 /* Find squared gains */
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H A D | main_FIX.h | 176 const opus_int32 invGains_Q16[ MAX_NB_SUBFR ], /* I Inverse quantization gains, one for each subframe */ 189 const opus_int32 gains[ MAX_NB_SUBFR ], /* I Quantization gains */ 206 /* Processing of gains */
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/external/libopus/celt/mips/ |
H A D | celt_mipsr1.h | 68 static const opus_val16 gains[3][3] = { local 81 g00 = MULT16_16_P15(g0, gains[tapset0][0]); 82 g01 = MULT16_16_P15(g0, gains[tapset0][1]); 83 g02 = MULT16_16_P15(g0, gains[tapset0][2]); 84 g10 = MULT16_16_P15(g1, gains[tapset1][0]); 85 g11 = MULT16_16_P15(g1, gains[tapset1][1]); 86 g12 = MULT16_16_P15(g1, gains[tapset1][2]);
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/external/webrtc/webrtc/modules/audio_processing/agc/legacy/ |
H A D | digital_agc.c | 30 // gains = round(2^16*10.^(0.05 * (MinGain + B * ( log(exp(-Knee*A)+exp(-Knee*B)) - log(1+exp(-Knee*B)) ) / log(1/(1+exp(Knee*B)))))); 31 // fprintf(1, '\t%i, %i, %i, %i,\n', gains); 33 // in = 10*log10(lvl); out = 20*log10(gains/65536); 300 // array for gains (one value per ms, incl start & end) 301 int32_t gains[11]; local 416 gains[0] = stt->gain; 457 gains[k + 1] = stt->gainTable[zeros] + (tmp32 >> 12); 507 if ((gains[k + 1] - stt->gainTable[0]) > 8388608) 510 tmp32 = (gains[k + 1] - stt->gainTable[0]) >> 8; 514 tmp32 = (gains[ [all...] |
/external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/batch/ |
H A D | ordinal_split_handler_test.py | 107 are_splits_ready2, partitions, gains, splits = ( 109 are_splits_ready, are_splits_ready2, partitions, gains, splits = ( 111 are_splits_ready, are_splits_ready2, partitions, gains, splits 143 expected_left_gain + expected_right_gain - expected_bias_gain, gains[0], 171 self.assertAllClose(0.0, gains[1], 0.00001) 242 are_splits_ready2, partitions, gains, splits = ( 244 are_splits_ready, are_splits_ready2, partitions, gains, splits = ( 246 are_splits_ready, are_splits_ready2, partitions, gains, splits 328 are_splits_ready2, partitions, gains, splits = ( 330 are_splits_ready, are_splits_ready2, partitions, gains, split [all...] |
H A D | categorical_split_handler_test.py | 94 are_splits_ready, partitions, gains, splits = ( 96 are_splits_ready, partitions, gains, splits = (sess.run( 97 [are_splits_ready, partitions, gains, splits])) 128 expected_left_gain + expected_right_gain - expected_bias_gain, gains[0], 152 self.assertAllClose(0.0, gains[1], 0.00001) 214 are_splits_ready, partitions, gains, splits = ( 216 are_splits_ready, partitions, gains, splits = (sess.run( 217 [are_splits_ready, partitions, gains, splits])) 279 are_splits_ready, partitions, gains, splits = ( 281 are_splits_ready, partitions, gains, split [all...] |
H A D | categorical_split_handler.py | 176 partition_ids, gains, split_infos = ( 194 return (are_splits_ready, partition_ids, gains, split_infos)
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H A D | ordinal_split_handler.py | 52 4.3) Find the gains for all bucket boundaries: 261 partition_ids, gains, split_infos = ( 277 return (are_splits_ready, partition_ids, gains, split_infos) 400 partition_ids, gains, split_infos = ( 417 return (are_splits_ready, partition_ids, gains, split_infos)
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/external/libxaac/decoder/ |
H A D | ixheaacd_acelp_info.h | 38 WORD32 gains[NUM_SUBFR_SUPERFRAME]; member in struct:__anon13131
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/external/libopus/celt/ |
H A D | celt.c | 198 static const opus_val16 gains[3][3] = { local 214 g00 = MULT16_16_P15(g0, gains[tapset0][0]); 215 g01 = MULT16_16_P15(g0, gains[tapset0][1]); 216 g02 = MULT16_16_P15(g0, gains[tapset0][2]); 217 g10 = MULT16_16_P15(g1, gains[tapset1][0]); 218 g11 = MULT16_16_P15(g1, gains[tapset1][1]); 219 g12 = MULT16_16_P15(g1, gains[tapset1][2]);
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/external/webrtc/webrtc/modules/audio_coding/codecs/ilbc/ |
H A D | cb_search.c | 56 int16_t gains[CB_NSTAGES+1]; local 184 gains[0] = 16384; 290 (int16_t)WEBRTC_SPL_ABS_W16(gains[stage]), stage, &gain_index[stage]); 346 gains[stage+1] = bestGain; 369 tmp = (int16_t)((gains[1] * gains[1]) >> 14); 373 tmpW32 = ((int32_t)(gains[1]-1))<<1;
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/external/tensorflow/tensorflow/contrib/boosted_trees/kernels/ |
H A D | split_handler_ops.cc | 177 context, context->allocate_output("gains", TensorShape({num_elements}), 180 tensorflow::TTypes<float>::Vec gains = gains_t->vec<float>(); variable 233 gains(root_idx) = 346 context, context->allocate_output("gains", TensorShape({num_elements}), 349 tensorflow::TTypes<float>::Vec gains = gains_t->vec<float>(); variable 386 // Split gains are evaluated for each pass at every threshold and the best 504 gains(root_idx) = 590 context, context->allocate_output("gains", TensorShape({num_elements}), 593 tensorflow::TTypes<float>::Vec gains = gains_t->vec<float>(); variable 640 gains(root_id [all...] |
/external/aac/libAACdec/src/ |
H A D | usacdec_acelp.h | 143 UCHAR gains[NB_SUBFR]; /**< gain index for each ACELP subframe */ member in struct:__anon243
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/external/webrtc/webrtc/modules/audio_processing/intelligibility/ |
H A D | intelligibility_enhancer.cc | 241 float* gains = gain_applier_.target(); local 243 gains[i] = 0.0f; 245 gains[i] = fmaf(filter_bank_[j][i], gains_eq_[j], gains[i]); 342 // Analytic solution for optimal gains. See paper for derivation.
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