1. Overview of Adaptive Multi-Rate Narrow Band (AMR-NB) Speech Codec
Presented by Peter

2. AMR Narrow Band
Adaptive Multi-Rate Codec for narrow band speech (AMR-NB)
Specified by 3GPP for GSM/3G Systems
Input: 8 kHz sampling rate, 13-bit PCM
20 ms frames, no overlap
8 modes + Comfort noise
Output bitrate from 4.75 – 12.2 kbps
Algebraic Code Excited Linear Prediction (ACELP) is used as speech codec

3. Frequency Response

4. Speech Encoder Pre-processing
Linear prediction analysis and quantization
Open-loop pitch analysis
Impulse response computation
Target signal computation
Adaptive codebook
Algebraic codebook
Quantization of the adaptive and fixed codebook gains
Memory update

5. Principles of the adaptive multi-rate speech encoder
Eight source codecs with bit-rates of 12.2, 10.2, 7.95, 7.40, 6.70, 5.90, 5.15 and 4.75 kbit/s
10th order linear prediction (LP), or short‑term, synthesis filter is used which is given by
The long‑term, or pitch, synthesis filter is given by
The pitch synthesis filter is implemented using adaptive codebook approach

6. ACELP

7. Pre-Processing Two pre‑processing functions
high‑pass filtering
signal down‑scaling – prevent overflow
A filter with a cut off frequency of 80 Hz is used

8. Linear Prediction Analysis
Frame is spit into four sub-frames
12.2 kbit/s mode
Performed twice per frame
30ms asymmetric window
No lookahead
10.2, 7.95, 7.40, 6.70, 5.90, 5.15, 4.75 kbit/s
Performed once per frame
5ms lookahead

9. Windowing and Auto-correlation Computation
12.2 kbit/s mode
Two different asymmetric windows
1st window concentrates on 2nd sub-frame
2nd window concentrates on 4th sub-frame

10. Windowing and Auto-correlation Computation
10.2, 7.95, 7.40, 6.70, 5.90, 5.15, 4.75 kbit/s
One asymmetric windows
Concentrates on 4th sub-frame
5ms (40 samples) lookahead

11. Auto-correlation Computation
Lag 0 to 10 is computed
is the windowed speech
60 Hz bandwidth expansion is used by lag windowing
is multiplied by the white noise correction factor which is equivalent to adding a noise floor at ‑40 dB

12. Levinson‑Durbin algorithm
by solving the set of equations
uses the following recursion:
The final solution is given as

13. LP to LSP conversion
The LP filter coefficients, are converted to the line spectral pair (LSP) representation for quantization and interpolation purposes
The LSPs are defined as the roots of the sum and difference polynomials
All roots of these polynomials are on the unit circle and they alternate each other
z=-1 and 1 are eliminated

14. LP to LSP conversion

15. Quantization of the LSP coefficients
12.2 kbit/s mode
Two sets of LSP are quantified using the representation in the frequency domain
1st order MA prediction is applied
two residual LSF vectors are jointly quantified using split matrix quantization (SMQ)
weighted LSP distortion measure is used in the quantization process
10.2, 7.95, 7.40, 6.70, 5.90, 5.15, 4.75 kbit/s modes
residual LSF vector is quantified using split vector quantization
weighted LSP distortion measure

16. Interpolation of the LSPs
12.2 kbit/s mode
interpolated LSP vectors at the 1st and 3rd subframes are given by
10.2, 7.95, 7.40, 6.70, 5.90, 5.15, 4.75 kbit/s modes
interpolated LSP vectors at the 1st, 2nd, and 3rd subframes are given by

17. Open‑loop pitch analysis
Performed twice per frame (each 10 ms) for 12.2k, 10.2k, 7.95k, 7.40, 6.70k, 5.90k bit/s modes
Performed once per frame for 5.15k, 4.75k bit/s modes
Filtering the pre-processed signal with a perceptual weighting filter
original
weighted
unit circle
Flat:
Tilted:

18. Impulse response computation
The impulse response, h(n) is computed each subframe
For the search of adaptive and fixed codebooks
Computed by filtering the vector of coefficients of the filter extended by zeros through the two filters and

19. Adaptive codebook
Adaptive codebook search is performed on a subframe basis
The parameters are the delay and gain of the pitch filter
The codebook contain entries taken from the previously synthesized excitation signal

20. Algebraic codebook Encode the random portion of the excitation signal
The periodic portion of the weighted residual is first removed. Only the random portion is remained to be coded by fixed codebook
Codebook search by minimize error between perceptual weighted input speech and reconstructed speech
Based on interleaved single-pulse permutation (ISPP) design
A few sparse impulse sequence that are phase-shifted version of each other
All the pulses have the same magnitude
Amplitudes are +1 or -1

21. Speech decoder Codebook parameter are decoded by table look up
LSP coefficients are interpolated and converted to LP coefficients
Excitation = sum of adaptive and fixed codebook vectors multiplied by their respective gains in each subframe
Speech = excitation through vocal tract filter.
Enhanced perceived quality by adaptive post-filtering.

22. Speech decoder

23. Synthesis model

24. Synthesis model To reconstruct speech A noise-like speech
A pitch filter model of the glottal vibrations
A linear prediction filter model of the vocal tract

25. Post‑processing Adaptive post-filtering High-pass filter
Cascade of two filters: a format postfilter and a tilt compensation filter
Updated every subframe of 5 ms
High-pass filter
Against undesired low frequency components
Cut-off frequency of 60 Hz is used
Up-scaling by a factor of 2 to compensate for the down-scaling by 2 which is applied to the input signal