EE 225D LECTURE ON MEDIUM AND HIGH RATE CODING. University of California Berkeley
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1 University of California Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Professors : N.Morgan / B.Gold EE225D Spring,1999 Medium & High Rate Coding Lecture 26 N.MORGAN / B.GOLD LECTURE
2 Quality, Robustness, Speaker I.D., Possible Vocoding of Other Sounds. Summary for Chapter 33 - Medium & High Rate Systems * Voice Excitation & Spectral Flattering * Voice - Excited Channel Vocoder * VELP & RELP * Wave form Coding using predictive methods.(adpcm)-(cvsd) * APC * Subband Coding Emphasis in an getting a good efficient repesentation of the excitation. N.MORGAN / B.GOLD LECTURE
3 *Multi pulse LPC Accent on Error Signal. * CELP Celp is a variation on APC. Representation of good Excitation is still the basic issue. * Reducing Codebook Search Time in CELP. * Back Ward Filtering * Multi Resolution Codebook Search * Partial Sequence Elimination * Tree Structured Delta Codebooks * Adaptive Codebooks * Linear Conbination Codebooks * Vector Sum Excited Linear Preduction * Adaptive Transform Coding N.MORGAN / B.GOLD LECTURE
4 Different Structures for Wide Band & Medium Band Digital System * Pure Waveform Coding Subband Coding Pure Waveform Coding * Pure Modelling on a channel by channel basis. * Hybrid Systems speech 0 f 1 Waveform Coding f 1 f 2 Waveform Coding + * Voice - Excited System Excitation derived from same band limited function of the speech. * Processing of the Error Signal to Produce a Band Limited Excitation Function. APC CELP Multi-Pulse Many Variation N.MORGAN / B.GOLD LECTURE
5 Pure Waveform Coding (Very Robust) Play Molly s tape. Possible Viewgraphs : Fig.33.8, 33.9, Sampling & Quantization. Local max construct ADPCM CUSD I II f Let s stick to pure PCM. from a perceptual viewpoint, fewer bits are needed to encode II, compared to I. B f f Each band is sampled and quantized. Important Point : if bandwidths are judiciously clean, sampling can be done at Nyquist rate. = 2B f s f n f ( n + 1) f No aliasing!, so original can be recovered. f N.MORGAN / B.GOLD LECTURE
6 Subband Coding I f Let s stick to pure PCM. II f From a perceptual Viewpoint, fewer bits are needed to encode II, compared to I. B Important Point: If bandwidths are judicialy clean, f sampling can be done at Nyquist rate. Each band is sampled and quantized. f f f s = 2B Fig n f ( n + 1) f f f No Aliasing! So original can be recovered. N.MORGAN / B.GOLD LECTURE
7 Voice -Excited Channel Vocoder (late 1950 s to early 1960 s) Motivations : (1) General Faling - Excitation Signal in Channel Vocoder was NOT Robust. (2) Possible Transmission of a Wide Band (Analog) Speech Signal (0-8kHz) throughan excisting Telephone Channel [ Hz]. * Intuitive grasp of the fact that baseband [0-900Hz], generally carried all the necessary excitation information for vocal channel vibrations. * A white noise same use a suitable excitatin for voiceless sounds. N.MORGAN / B.GOLD LECTURE
8 Original Idea Analysis Speech Channel Vocoder Analyzer Base Band Filter Spectral Hz Speech Signal Base Band Speech Synthesis Hz Base Band Speech Non-Linear Hz Vocoder Synthetic Distoration Synthesizer Speech Problem : Distortion of the excitation spectrum. * Intuitive grasp of the fact that baseband [0-900Hz], generally carried all the necessary excitation information for vocal channel vibrations. * A white noise same use a suitable excitatin for voiceless sounds. N.MORGAN / B.GOLD LECTURE
9 In early 1960 s, Schroeder, David et al at BTL, introduced spectral flattering -got rid of spectral distortion [more or less]. Base Band Signal Simple non-linearity (rectifier) Spectral Flattening f Result of non-linearnity distortion products frequencies are harmonics of the fundamental frequency. N.MORGAN / B.GOLD LECTURE
10 In the late 1960 s, schroeder and Atal introduced APC -Adaptive Predictive Coding. Long Term Predictor Prediction Sample to be predicted Previous Samples time N.MORGAN / B.GOLD LECTURE
11 Two types of prediction. Predicted Value ŷ( n) = αyn ( T) = yn ( ) + en ( ) so e 1 ( n) = yn ( ) + αy( n M) e 1 ( n) Perform LPC Analysis on e 1 By transmitting e 1 ( n) ( n) = a 1 e 1 ( n 1) + a 2 e 1 ( n 2) + a k e 1 ( n k) + e 2 a 1, a 2, a k and α, M n Major Assumption - ( n) is so small e 2 that it can be quantized to 1 bit. BUT SENT at the sampling rate. N.MORGAN / B.GOLD LECTURE
12 Even a ONE bit error signal results in a large bit rate. If sampling rate is 8kHz, then transmission of error signal costs 8kbs. Addition of transmitting d, M, a k s sould be another 2kbs. Pitch Detection If pitch is wrong, first error signal e 1 ( n) is big. Early APC Systems Operated at 9600bps. Major Research Efforts : Reduction of Error Signal Bit Rate. N.MORGAN / B.GOLD LECTURE
13 Key to Error Signal Reduction. * LPC - Error Signal is eliminated and replaced by standard Excitation Signals. (like Channel Vocoder) * RELP - Residual Excited linear Prediction. Low Pass Filter of error Signal - reduced sampling rate. still one bit quantization. * VELP - Voice-Excited LP. So error signal rate can be reduced [hopefully]. They aimed for 4800 bps. N.MORGAN / B.GOLD LECTURE
14 As computer speeds increased, New sptions became available for Basic Philosophy - Analysis by Synthesis real-time Coding of the Error Signal. * Transmitting system has both analyzer and synthesizer available. * So Synthetic Speech can be generated at the transmitter. * Using same criteria, the synthetic speech is compared sequentially with the actual speech [perhaps every frame, or every n frames] and synthesizer parameters obtained by analysis VARIED to obtain a GOOD fit between ACTUAL SPEECH vs. SYNTHESIZED SPEECH. we encountered this idea * So the best parameters are sent. in the Setevens Halle concept in chapter 17. N.MORGAN / B.GOLD LECTURE
15 Basic Idea - Replace the one-bit error signal of APC with a vector quantized error signal. Analyzer Store of M Sequences, each of length one frame. Speech sn ( ) Change Address LPC Analyzer Vocal Tract Parameters LPC Synthetic Speech Synthesis ŝ( n) mean squered difference Transmit address of best of the M sequences transmit the Vocal Tract Parameters. Receiver This is an example of VQ. Store of M Sequences, each of length one frame. Vocal Tract Parameters best exciter LPC Synthesis Synthetic Speech best address N.MORGAN / B.GOLD LECTURE
16 Problems discussed in Chapter 33 * How to create the stone? * Perceptual weighting filter. * Delay * Reduction of Codebook Search. [In 20ms, the analyzer must performe complete analysis-synthesis many times in a single frame.] So computer speed must be such that MANY systems can opearate in real time SIMULTANEOUSLY. * Adaptive Coding.[ Storage is adaptive to a different speaker] N.MORGAN / B.GOLD LECTURE
17 sn ( ) _ en ( ) ê( n) Q + ŝ( n) z 1 z 1 ê( n) Figure 33.7 : Differential Pulse Code Modulation. sn ( ) en ( ) _ z 1 Quantized error Signal ê( n) Adaptive Quantizer Format Q(V) V Format ê( n) V _ + ŝ( n) z 1 Rectification Low-Pass Filtering Figure 33.8 : Adaptive Differential Pulse Code Modulation. N.MORGAN / B.GOLD LECTURE
18 sn ( ) en ( ) Σ Hard Limiter ê( n) Channel z 1 z 1 z 1 ŝ( n 1) a 1 z 1 M Analyzer Mn ( ) = f(ê( n), ê( n 1), a Σ 1 ê( n 2)) z 1 z 1 ŝ( n) = a 1 ŝ( n 1) + Mn ( ) Transmitter M Analyzer Mn ( ) Σ ŝ( n) Receiver Figure 33.9 : Continuously Variable Slope Delta Modulation. a 1 = N.MORGAN / B.GOLD LECTURE
19 Speech sn ( ) 1 Pz ( ) + + _ Quantized Error Signal Q Pz ( ) Sn ( ) Pz ( ) ê( n) Pz ( ) Analyzer Parameter Coder Figure : Rudimentary Linear Prediction Concept N.MORGAN / B.GOLD LECTURE
20 e 1 ( n) + e _ H 2 ( n) 1 K 1 2:1 H 1 H 2 2:1 2:1 + xn ( ) ( n) s' ( n) e 4 1:2 1:2 K 1 K 2 1:2 _ H 2 2:1 H 1 H 2 2:1 2:1 e 3 + K 1 ( n) + 1:2 1:2 K 2 _ 1:2 K 2 Figure : Four Channel Subband Coder with Quadrature Mirror Filters. N.MORGAN / B.GOLD LECTURE
21 OUTPUT Figure 33.2 : Zig-Zag Network N.MORGAN / B.GOLD LECTURE
22 Figure 33.1 : Spectral Flattening of the Base-Band Signal Frequency N.MORGAN / B.GOLD LECTURE
23 Output Input Hand Limiter Input-Output Characteristic Fig. 33.1b Speech Low-Pass Filter Half-Wave Fig. 33.1a Rectifier Bandpass Hand Filter Limiter Bandpass Hand Filter Limiter Bandpass Hand Filter Limiter Figure 33.3 : Implementation of Spectral Flattening. Fig. 33.1c N.MORGAN / B.GOLD LECTURE
24 Input One Bit Σ Speech Quantizer q en ( ) M α z + Σ - Σ M α z s n Σ First Error Signal a k z k LPC Analysis Pitch Analysis Σ a 1 a 2 a 4 q α M Coding and Packing to RCVR Adaptive Predictive Coding of Speech N.MORGAN / B.GOLD LECTURE
25 Input Speech LPC Analysis Low-Pass Filter Coding LPC High-Pass Synthesis Filter Formatting Excitation Signal Transmission Low-Pass Distotion Spectrum Decoding Filter Network Flattener + Output Speech (a) VELP (Voice-Excited Linear Prediction) Input LPC Speech Analysis Error Signal Low-Pass Filter LPC parameter Coding LPC Synthesis Formatting Excitation Signal Transmission Low-Pass Distotion Spectrum Decoding Filter Network Flattener Output Speech (b) RELP (Residual-Excited Linear Prediction) Block Diagrams of VELP and RELP. N.MORGAN / B.GOLD LECTURE
26 Spectra at different nodes in the VELP algorithm. N.MORGAN / B.GOLD LECTURE
27 Innovation White + Fine Structure (Pitch) + Spectral Envelope (Formants) Speech Long Delay Short Delay Predictor Predictor Figure 1 : Speech Synthesis Model with Short and Long Delay Predictors. Innovation White Perceptual Error + Long Delay Short Delay Predictor Predictor Average Figure 2 : Block Diagram Illustrating the Procedure for Selecting the Optimum innovation Sequence. N.MORGAN / B.GOLD LECTURE Square Ŝn Perceptual Weighting Filter Origianl Speech Sn Signal Instantaneous _ Objective Error
28 Analysis by Synthesis How to create the store? Reduction of delay. Reduction of Codebook Search Adaptive Codebook. APC 10,000bps. Bessie Smith Louis Armstong. N.MORGAN / B.GOLD LECTURE
29 APC - Adaptive Preductor Coder Late 1960 s yn ( M) ŷ( n) M pitch e 1 ( n) Analysis e 1 ( n) LPC e 2 ( n) ŷ( n) = αyn ( M) = yn ( ) + e 1 ( n) e 1 e 1 ( n) = yn ( ) + αy( n M) ( n) = a 1 e 1 ( n 1) + a 2 e 1 ( n 2) + + e 2 ( n) i bit N.MORGAN / B.GOLD LECTURE
30 Channel Vocoder Analyzer Hz Parameter Vocodar Synthesizer Low-Pass Filter 0-800Hz Baseband Non-Linear Distortion 0-800Hz Impossible to get Flat Spectrum. 10,000 bits per second. N.MORGAN / B.GOLD LECTURE
31 Subband Coding 0 f 1 f 1 f 2 f 1 f 2 f n f n k bits 20-30k bits n f ( n + 1) f 0 f bits f 1 f 2 2bits 4000 N.MORGAN / B.GOLD LECTURE
32 Medium & High Rate Systems Quality Robustness Possible Vocoding of Sounds other than Speech Speaker I.D. Waveform - PCM - 8kHz, 8bits 64kbits. (Subband Coding) DPCM ADPCM CVSD Basic Issue Efficient Representation of the Excitation. Voice-Excited Systems Prediction - APC CELP Multi-Pulse LPC Channel Vocoders N.MORGAN / B.GOLD LECTURE
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