1. CELLULAR COMMUNICATIONS 5. Speech Coding

2. Low Bit-rate Voice Coding  Voice is an analogue signal  Needed to be transformed in a digital form (bits)  Speech signal is not random=>can be encoded using fewer bits as compared to random signal  If bits representing 1sec of speech can transferred over wireless channel during 200ms=> can pack 5 signals into the channel  For a handset transmitting less bits is alsoe means longer battery life

3. Requirement for speech coding  Can distort a speech a little bit (lossy) but should preserve acceptable quality  Shouldn’t be to complex  Use less power  Use less circuits  Reduce delay

4. Hierarchy of speech coders

5. Waveform Coders vs. VOCODERS  Waveform coders  Approximate any acoustic signal  VOCODERS  Based on prior knowledge of the signal  Speech signals are very special signals

6. Speech signals  Not all levels of a speech signal are equally likely  High probabilities of very low amplitudes  Significant probability of very high amplitudes  Monotonically decreasing probabilities of amplitudes between these two extremes  Speech is predictable  The next value of a speech signals can be predicted with large probability and fair precision from the past samples

7. Speech in frequency domain  Power of high frequency components is small  High frequency components when present are very important for speech quality

8. Sampling and quantization  Speech signal is analog, measured at infinitely many time instances and infinitely many possible values  Sampling: measure signal at finite time instances (sampling interval)  Quantization: approximate infinitely many possible values by finite number of possible values (e.g. 8 bits)

9. Uniform quantization  Divide the range of all possible values into finite number of equal intervals  Assign single quantization value to all values within the interval

10. Non-uniform quantization  Divide the range of all possible values into finite number of unequal but equally probable intervals  Logarithmic quantization: smaller intervals at low amplitudes  Different weight to low values  US:  -Law  Europe: A-low

11.  -Law

12. A-law

13. Adaptive quantization  Adjust to input signal power

14. Rate-Distortion Theorem  Shannon: There existing a mapping from source waveform to code words such that for given distortion (error) D, R(D) bits per sample is sufficient to restore signal with an average distortion arbitrary close to D  R(D) is called rate distortion formula (achievable low bound)  Scalar quantization does not achieve this bound

15. Vector quantization  Encode a segment of sampled analog signal (e.g. L samples)  Use codebooks of n vectors  Segment all possible samples of dimension L into areas of equal probability  Very efficient at very low rates( R=0.5 bits per sample)

16. Learning codebook  LBG: Split areas (double codebook)

17. Adaptive Differential Pulse Code Modulation  PCM  Each sample representing by its amplitude (8 bits)  Standard telephony: 8K samples per second, 8 bit per sample= 64kbps  DPCM  Encode only difference from previous sample  Smaller differences are more often  Use less bits to represent smaller differences(4 bits) but more bits (10 bits) to represent larger differences

18. DPCM and prediction

19. ADPCM  Use more complex prediction in a transmitter/receiver to estimate next sample value  Transmitter send only difference between estimation and real value  Lossy codec: transmit approximate differences  Hopefully difference will be small

20. Frequency Domain Coding of Speech  Divide speech signal into a set of frequency components  Quantize and encode each component separately  Control number of bits/quality allocate to each band

21. Sub-band coding  Human ear does not detect error at all frequencies equally well

22. SBC

23. Vocoders  Model speech signal generation process  Transmitter analyze the voice signal according to assumed model  Transmitter sends parameters driveled from the analysis  Receiver synthesize voice based on received parameters  Vocoders are much more complex that waveform coders but achieve higher economy in a bit rate

24. Human Vocal Tract

25. Voice Generation Model

26. LPC

27. Advanced codecs  CELP  Transmitter/Receiver share common pitch codebook  Search for most suitable pitch code  RELP  Transmit model parameters  Also transmit Residual(differences) signal

28. Mean Opinion Score Quality Rating

29. Codec MOS rating