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									   Digital Signal Processing:
An Introduction and Some Examples of its
              Everyday Use

        Dr D. H. Crawford
    EPSON Scotland Design Centre
                Contents
• What is DSP?
• What is DSP used for?
  – Speech & Audio processing
  – Image & Video processing
  – Adaptive filtering
• DSP Devices and Architectures
• DSP at EPSON Scotland Design Centre
• Summary & Conclusions

                     Slide 2
                      What is DSP?
   • Digital Signal Processing – the processing
     or manipulation of signals using digital
     techniques


                          Digital
Input                                             Output
Signal
          ADC             Signal      DAC         Signal
         Analogue        Processor   Digital to
         to Digital                  Analogue
         Converter                   Converter




                           Slide 3
What is DSP Used For?




                   …And much more!
         Slide 4
  Speech Processing




• Speech coding/compression
• Speech synthesis
• Speech recognition

            Slide 5
Some Properties of Speech



    The blue--- s---p--o---------t i-s--on--the-- k--ey a---g--ai----n------




                                “e” in “again”
                                “ee”in “blue”
                               “oo” inin“spot”
                                 “s”
                                 “k” “key”
                                 “o” in “key”




                                   Slide 6
         Some Properties of Speech
                                             Vowels


“oo” in “blue”             “o” in “spot”               “ee” in “key”         “e” in “again”


                             •Quasi-periodic
                             •Relatively high signal power

                                           Consonants


                 “s” in “spot”                                “k” in “key”

                             •Non-periodic (random)
                             •Relatively low signal power

                                             Slide 7
           Speech Coding

                               TRAU




MSC
      64 kbits/s
                                             22.8 kbits/s
                   BSC
                         13 kbits/s


                                       BTS




                             Slide 8
Speech Coding – Linear Prediction
• Try to predict the current sample value;
• Transmit the prediction error.

 s(n)
                       +       d(n)
                  –                    …
                                                d(n)
        A(z)                                              
               se(n)                                   +                      sr(n)
                                                           +
                                                                       A(z)
                                                               se(n)




                                      Slide 9
         Speech Coding – Vocoder
                                                                             Encoder
                                                  Original Speech
    Analysis:
    • Voiced/Unvoiced decision
    • Pitch Period (voiced only)
    • Signal power (Gain)




 Pitch                                                                       Decoder
Period                               Signal Power
          Pulse Train          V/U
                                                        Vocal Tract
                                          G               Model

                                                                      Synthesized Speech
                                              LPC-10:
         Random Noise

                                       Slide 10
        Text-to-Speech Synthesis
Input       To be or
 text       not to be
            that is the                      Tu bee awr          phonetic form
            question                         nawt tu bee
                                             dhat iz dhe
                                             kwestchun

             Text
         normalization           Parsing              Pronunciation
          expands             semantic &             phonetic description
          abbreviations       syntactic „parts       of each word, dictionary
          dates, times,       of speech‟             with letter-to-sound
          money..etc          analysis of text       rules as a back up



             Prosody           Waveform                Synthesized
               rules           generation                speech
           Apply word         Phonetic-to-
           stress, duration   acoustic
           and pitch          transformation

 Text-to-speech synthesis sounds very natural these days.
                                  Slide 11
    Speech Synthesis Applications

• Speaking clocks
• Spoken (variable) announcements
• Talking emails + talking heads for mobile
• Synthesis of location-based information
  (e.g. traffic information)
• Interactive systems (e.g. catalogue ordering,
  Yellow Pages, ...)


                     Slide 12
    Speech/Speaker Recognition
• Speech Recognition – What has been spoken?
  – Speaker dependent – Recognition system trained
    for a particular person‟s voice.
  – Speaker independent – Recognition system
    expected to deal with a wide variety of speakers.
• Speaker Recognition – Who has spoken?
• Not easy…
      Sometimestherearenogapsbetweenwords.
      Sometim esthereareg aps inthe mid dleofwords.
      Accents, dialects and Stress eggsist.
                         Slide 13
         Speech Recognition System


                           Phoneme          Word          Semantic
                            models       pronunciation    knowledge



            Feature      Phoneme           Word           Sentence
speech     extraction   recognition     recognition      recognition        decision



                                                   Syntactic           Dialogue
                                                   knowledge           knowledge




                                  Slide 14
                Digital Audio

• Standard music CD:
  –   Sampling Rate: 44.1 kHz
  –   16-bit samples
  –   2-channel stereo
  –   Data transfer rate = 21644,100 = 1.4 Mbits/s
  –   1 hour of music = 1.43,600 = 635 MB



                        Slide 15
       Audio Coding (Cont‟d)
• Key standards:
  – MPEG: Layers I, II, and III (MP3); AAC.
     • used in DAB, DVD
  – Dolby AC3, Dolby Digital, Dolby Surround.
• Typical bit rates for 2-channel stereo:
  – 64kbits/s to 384 kbits/s.
• Subband- or transform-based, making use
  of perceptual masking properties.

                       Slide 16
            Audio Coding (Cont‟d)
• Typical 3/2 multichannel stereo configuration:
                                                        Surround
    Right
                                                         Right

   Centre


     Left                                               Surround
                                                          Left

• 5.1 channels (3/2) with LFE channel:
   – Left, Right, Centre,
   – Left Surround, Right Surround,
   – Low Frequency Effects (LFE) (Reduced Bandwidth).
       • LFE loudspeaker can, in general, be placed anywhere in the
         listening room.
                               Slide 17
         Audio Coding – Masking
• Auditory Masking:
     – Spectral: Strong frequency components mask weaker
       neighbouring frequency components.
     – Temporal: Strong temporal events mask recent and
       future events.

         Spectral Masking                                Temporal Masking
SPL/dB                                      SPL/dB




                    1       freq/kHz              10ms              160ms   time



                                       Slide 18
            Masking Example


     60




     50




     40
dB




     30




     20




     10
      200     300   400       500    600   700   800
                              Hz




                          Slide 19
                   Image/Video
• Still Image Coding:
   – JPEG (Joint Photographic Experts Group):
      • Discrete Cosine Transform (DCT) based
   – JPEG2000: Wavelet Transform based
• Video Coding:
   – MPEG (Moving Pictures Experts Group):
      • DCT-based,
      • Interframe and intraframe prediction,
      • Motion estimation.
   – Applications: Digital TV, DVD, etc.


                              Slide 20
             JPEG Example
                 Original




JPEG (4:1)                   JPEG (100:1)




                  Slide 21
             Adaptive Filtering
• Self-learning: Filter coefficients adapt in response
  to training signal.
                                             d(n)

                                             +
      x(n)          W(z)                –          e(n)
                                      y(n)


• Filter update: Least Mean Squares (LMS) algorithm

               w(n 1)  w(n)  2e(n)x(n)
                           Slide 22
 Adaptive Filtering Applications

• Echo cancellation (telephone lines)
   – Used in modems (making Internet access possible!!)
• Acoustic echo cancellation
   – Hands-free telephony
• Adaptive equalization
• Active noise control
• Medical signal processing
   – e.g. foetal heart beat monitoring


                            Slide 23
    Some Other Application Areas
• Image analysis, e.g:
    – Face recognition,
    – Optical Character Recognition (OCR);
• Restoration of old image, video, and audio signals;
• Analysis of RADAR data;
• Analysis of SONAR data;
• Data transmission (modems, radio, echo
  cancellation, channel equalization, etc.);
• Storage and archiving;
• Control of electric motors.

                           Slide 24
   DSP Devices & Architectures
• Selecting a DSP – several choices:
   – Fixed-point;
   – Floating point;
   – Application-specific devices
     (e.g. FFT processors, speech recognizers,etc.).
• Main DSP Manufacturers:
   – Texas Instruments (http://www.ti.com)
   – Motorola (http://www.motorola.com)
   – Analog Devices (http://www.analog.com)



                            Slide 25
      Typical DSP Operations
• Filtering                                           L 1
• Energy of Signal                         y ( n)     ai x(n  i)
                                                      i 0
• Frequency transforms


                Pseudo C code
                for (n=0; n<N; n++)
                {
                  s=0;
                  for (i=0; i<L; i++)
                  {
                    s += a[i] * x[n-i];
                  }
                  y[n] = s;
                }



                                Slide 26
Traditional DSP Architecture

       X RAM     x(n-i)                 ai   Y RAM



                    Multiply/Accumulate




                          Accumulator




                             y(n)


N.B. Most modern DSPs have more advanced features.
                            Slide 27
DSP at EPSON




      “Energy-saving Firmware”
  EPSON Scotland Design Centre develops a
   broad range of technologies to minimize
    power consumption and maximize cost
   effectiveness in mobile DSP applications.


       Slide 28
                      SDC Core Skills
     DSP               Speech                 Audio                   Mobile           Services

System modelling     Speech compression          MP3            Baseband processing   Administration

 Firmware design     Speech Recognition   Other digital audio      Channel coding       CAD Tools

System Integration     Speech synthesis      Performance           AMR Coding            Computer
                                             Assessment                                     &
                                                                                        Networking
CPU (Oak, ARM)       Speech enhancement


    H/w & S/w          Speech Testing
    Co-design




                       System on Chip (SoC)




                                            Slide 29
SDC Firmware Development
         Algorithm
         Definition

        Floating-point
             and             COSSAP
         Fixed-point         Matlab ...
        Co-Simulation

         Co-Design           Behavioural,
                             RTL, Logic ...

Implementation        Co-Verification MCU, DSP ...

     Product Development        With Barcelona and Tokyo
                                     Design Centres

                         Slide 30
        Summary & Conclusions
• DSP used in a wide range of everyday applications
• Looked at:
   – Speech coding; Speech synthesis & recognition;
   – Image/Video;
   – Adaptive filtering.
• Other areas include:
   –   Image analysis (e.g. face recognition, OCR, etc.);
   –   RADAR/SONAR;
   –   Data transmission and reception;
   –   And many more…..!!

                             Slide 31

								
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