Tech-
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Overview
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4‑5x
Content for
TS 26.445
Word version: 16.1.1
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5
Functional description of the encoder
5.1
Common processing
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5
Functional description of the encoder
Word‑p. 25
5.1
Common processing
5.1.1
High-pass Filtering
5.1.2
Complex low-delay filter bank analysis
5.1.2.1
Sub-band analysis
5.1.2.2
Sub-band energy estimation
Word‑p. 26
5.1.3
Sample rate conversion to 12.8 kHz
Word‑p. 27
5.1.3.1
Conversion of 16, 32 and 48 kHz signals to 12.8 kHz
5.1.3.2
Conversion of 8 kHz signals to 12.8 kHz
5.1.3.3
Conversion of input signals to 16, 25.6 and 32 kHz
Word‑p. 29
5.1.4
Pre-emphasis
5.1.5
Spectral analysis
Word‑p. 30
5.1.5.1
Windowing and DFT
5.1.5.2
Energy calculations
Word‑p. 31
5.1.6
Bandwidth detection
Word‑p. 32
5.1.6.1
Mean and maximum energy values per band
5.1.7
Bandwidth decision
Word‑p. 34
5.1.8
Time-domain transient detection
Word‑p. 37
5.1.9
Linear prediction analysis
Word‑p. 38
5.1.9.1
LP analysis window
5.1.9.2
Autocorrelation computation
5.1.9.3
Adaptive lag windowing
Word‑p. 39
5.1.9.4
Levinson-Durbin algorithm
5.1.9.5
Conversion of LP coefficients to LSP parameters
Word‑p. 40
5.1.9.6
LSP interpolation
Word‑p. 41
5.1.9.7
Conversion of LSP parameters to LP coefficients
5.1.9.8
LP analysis at 16kHz
Word‑p. 42
5.1.10
Open-loop pitch analysis
Word‑p. 43
5.1.10.1
Perceptual weighting
5.1.10.2
Correlation function computation
Word‑p. 44
5.1.10.3
Correlation reinforcement with past pitch values
Word‑p. 45
5.1.10.4
Normalized correlation computation
Word‑p. 46
5.1.10.5
Correlation reinforcement with pitch lag multiples
5.1.10.6
Initial pitch lag determination and reinforcement based on pitch coherence with other half-frames
Word‑p. 47
5.1.10.7
Pitch lag determination and parameter update
Word‑p. 48
5.1.10.8
Correction of very short and stable open-loop pitch estimates
Word‑p. 49
5.1.10.9
Fractional open-loop pitch estimate for each subframe
Word‑p. 51
5.1.11
Background noise energy estimation
Word‑p. 52
5.1.11.1
First stage of noise energy update
5.1.11.2
Second stage of noise energy update
Word‑p. 54
5.1.11.2.1
Basic parameters for noise energy update
5.1.11.2.2
Spectral diversity
Word‑p. 55
5.1.11.2.3
Complementary non-stationarity
5.1.11.2.4
HF energy content
Word‑p. 56
5.1.11.2.5
Tonal stability
5.1.11.2.6
High frequency dynamic range
Word‑p. 60
5.1.11.2.7
Combined decision for background noise energy update
5.1.11.3
Energy-based parameters for noise energy update
Word‑p. 62
5.1.11.3.1
Closeness to current background estimate
5.1.11.3.2
Features related to last correlation or harmonic event
5.1.11.3.3
Energy-based pause detection
Word‑p. 63
5.1.11.3.4
Long-term linear prediction efficiency
5.1.11.3.5
Additional long-term parameters used for noise estimation
Word‑p. 64
5.1.11.4
Decision logic for noise energy update
Word‑p. 65
5.1.12
Signal activity detection
Word‑p. 68
5.1.12.1
SAD1 module
Word‑p. 69
5.1.12.1.1
SNR outlier filtering
Word‑p. 71
5.1.12.2
SAD2 module
Word‑p. 72
5.1.12.3
Combined decision of SAD1 and SAD2 modules for WB and SWB signals
Word‑p. 75
5.1.12.4
Final decision of the SAD1 module for NB signals
5.1.12.5
Post-decision parameter update
Word‑p. 76
5.1.12.6
SAD3 module
Word‑p. 77
5.1.12.6.1
Sub-band FFT
5.1.12.6.2
Computation of signal features
Word‑p. 78
5.1.12.6.3
Computation of SNR parameters
Word‑p. 81
5.1.12.6.4
Decision of background music
Word‑p. 83
5.1.12.6.5
Decision of background update flag
5.1.12.6.6
SAD3 Pre-decision
Word‑p. 84
5.1.12.6.7
SAD3 Hangover
Word‑p. 86
5.1.12.7
Final SAD decision
5.1.12.8
DTX hangover addition
Word‑p. 88
5.1.13
Coding mode determination
Word‑p. 90
5.1.13.1
Unvoiced signal classification
Word‑p. 91
5.1.13.1.1
Voicing measure
Word‑p. 92
5.1.13.1.2
Spectral tilt
5.1.13.1.3
Sudden energy increase from a low energy level
Word‑p. 93
5.1.13.1.4
Total frame energy difference
Word‑p. 94
5.1.13.1.5
Energy decrease after spike
5.1.13.1.6
Decision about UC mode
Word‑p. 95
5.1.13.2
Stable voiced signal classification
Word‑p. 96
5.1.13.3
Signal classification for FEC
5.1.13.3.1
Signal classes for FEC
Word‑p. 97
5.1.13.3.2
Signal classification parameters
5.1.13.3.3
Classification procedure
Word‑p. 98
5.1.13.4
Transient signal classification
Word‑p. 99
5.1.13.5
Modification of coding mode in special cases
Word‑p. 100
5.1.13.6
Speech/music classification
Word‑p. 101
5.1.13.6.1
First stage of the speech/music classifier
5.1.13.6.2
Scaling of features in the first stage of the speech/music classifier
Word‑p. 103
5.1.13.6.3
Log-probability and decision smoothing
Word‑p. 104
5.1.13.6.4
State machine and final speech/music decision
Word‑p. 105
5.1.13.6.5
Improvement of the classification for mixed and music content
Word‑p. 108
5.1.13.6.6
Second stage of the speech/music classifier
Word‑p. 112
5.1.13.6.7
Context-based improvement of the classification for stable tonal signals
Word‑p. 114
5.1.13.6.8
Detection of sparse spectral content
Word‑p. 118
5.1.13.6.9
Decision about AC mode
Word‑p. 120
5.1.13.6.10
Decision about IC mode
5.1.14
Coder technology selection
5.1.14.1
ACELP/MDCT-based technology selection at 9.6kbps, 16.4 and 24.4 kbps
Word‑p. 121
5.1.14.1.1
Segmental SNR estimation of the MDCT-based technology
5.1.14.1.2
Segmental SNR estimation of the ACELP technology
Word‑p. 127
5.1.14.1.3
Hysteresis and final decision
Word‑p. 128
5.1.14.2
TCX/HQ MDCT technology selection at 13.2 and 16.4 kbps
Word‑p. 129
5.1.14.3
TCX/HQ MDCT technology selection at 24.4 and 32 kbps
Word‑p. 131
5.1.14.4
TD/Multi-mode FD BWE technology selection at 13.2 kbps and 32 kbps
Word‑p. 134