Transcript Digital Signal Processing:

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
Input
Signal
ADC
Analogue
to Digital
Converter
Digital
Signal
Processor
Slide 3
DAC
Digital to
Analogue
Converter
Output
Signal
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------
“oo”
in
“blue”
“e”
“ee”
“o”
“s”
“k”in
in
in
in“again”
“spot”
“key”
“key”
Slide 6
Some Properties of Speech
Vowels
“oo” in “blue”
“o” in “spot”
“ee” in “key”
•Quasi-periodic
•Relatively high signal power
Consonants
“s” in “spot”
“k” in “key”
•Non-periodic (random)
•Relatively low signal power
Slide 7
“e” in “again”
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)
A(z)
–
se(n)
+

d(n)
…
d(n)
+

sr(n)
+
se(n)
Slide 9
A(z)
Speech Coding – Vocoder
Encoder
Original Speech
Analysis:
• Voiced/Unvoiced decision
• Pitch Period (voiced only)
• Signal power (Gain)
Decoder
Pitch
Period
Signal Power
Pulse Train
V/U
Vocal Tract
Model
G
Random Noise
LPC-10:
Slide 10
Synthesized Speech
Text-to-Speech Synthesis
Input
text
To be or
not to be
that is the
question
Tu bee awr
nawt tu bee
dhat iz dhe
kwestchun
Text
normalization
Parsing
expands
abbreviations
dates, times,
money..etc
semantic &
syntactic ‘parts
of speech’
analysis of text
Prosody
rules
Apply word
stress, duration
and pitch
Waveform
generation
Phonetic-toacoustic
transformation
phonetic form
Pronunciation
phonetic description
of each word, dictionary
with letter-to-sound
rules as a back up
Synthesized
speech
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
models
speech
Feature
extraction
Phoneme
recognition
Word
pronunciation
Word
recognition
Semantic
knowledge
Sentence
recognition
Syntactic
knowledge
Slide 14
decision
Dialogue
knowledge
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
Surround
Left
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
Slide 18
160ms
time
Masking Example
60
dB
50
40
30
20
10
200
300
400
500
Hz
Slide 19
600
700
800
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
• Energy of Signal
• Frequency transforms
y ( n) 
L 1
 ai x(n  i)
i 0
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
ai
x(n-i)
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
Administration
System modelling
Speech compression
MP3
Baseband processing
Firmware design
Speech Recognition
Other digital audio
Channel coding
CAD Tools
System Integration
Speech synthesis
Performance
Assessment
AMR Coding
Computer
&
Networking
CPU (Oak, ARM)
H/w & S/w
Co-design
Speech enhancement
Speech Testing
System on Chip (SoC)
Slide 29
SDC Firmware Development
Algorithm
Definition
Floating-point
and
Fixed-point
Co-Simulation
COSSAP
Matlab ...
Behavioural,
RTL, Logic ...
Co-Design
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