Content for TS 26.445 Word version: 16.1.1
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
5.1.3 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
5.1.6 Bandwidth detection Word‑p. 32
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
