SlideShare una empresa de Scribd logo
1 de 21
DIGITAL AUDIO AND VIDEO
Sahil Punni
7/10/2014
1
CONTENTS
 Audio
 How we hear Sound?
 Basic Sound Concepts
 Computer Representation of Audio
 Audio Encoding
 Audio Formats
 Video Encoding
 Video Formats
 Conclusion
 Additionals : Digital Audio and Video Editing
Softwares Explained
7/10/2014
2
AUDIO
 Sound is a continuous wave that travels through the
air.
 The wave is made up of pressure differences.
7/10/2014
3
HOW DO WE HEAR SOUND?
7/10/20144
BASIC SOUND CONCEPTS
 Frequency represents the number of periods in a
second (measured in hertz, cycles/second)
 Human hearing frequency range: 20 Hz - 20 kHz
(audio), voice is about 500 Hz to 2 kHz.
 Amplitude of a sound is the measure of
displacement of the air pressure wave from its
mean.
7/10/20145
COMPUTER REPRESENTATION OF AUDIO
• Speech is analog in nature and it is converted to digital
form by an analog-to-digital converter (ADC).
• A transducer converts pressure to voltage levels.
• Convert analog signal into a digital stream by discrete
sampling
• Discretization both in time and amplitude (quantization)
7/10/2014
6
AUDIO ENCODING (1)
Audio Waves Converted to Digital
• electrical voltage input
• sample voltage levels at intervals to get a vector of values: (0, 0.2, 0.5, 1.1, 1.5,
2.3, 2.5, 3.1, 3.0, 2.4,...)
• A computer measures the amplitude of the waveform at regular time intervals to
produce a series of numbers (samples).
• The ADC process is governed by various factors such as sample rate and
quantization: binary number as output
7/10/2014
7
AUDIO ENCODING (2)
• Sampling Rate: rate at which a continuous wave is
sampled (measured in Hertz)
• Examples: CD standard - 44100 Hz, Telephone
quality - 8000 Hz
• The audio industry uses 5.0125 kHz, 11.025 kHz,
22.05 kHz, and 44.1 kHz as the standard sampling
frequencies. These frequencies are supported by
most sound cards.
7/10/2014
8
AUDIO ENCODING (3)
 The best-known technique for voice digitization is
Pulse-Code Modulation (PCM).
 Voice 4000 Hz
What is the PCM sampling rate?
 PCM provides analog samples which must be
converted to digital representation. Each of these
analog samples must be assigned a binary code.
Each sample is approximated by being quantized as
explained next.
7/10/2014
9
AUDIO ENCODING (4)
 Quantization (sample precision): the resolution of
a sample value.
Samples are typically stored as raw numbers (linear
PCM format) or as logarithms (u-law or A-law)
Quantization depends on the number of bits used
measuring the height of the waveform
Example: 16-bit CD quality quantization results in over
65536 values
7/10/2014
10
AUDIO FORMATS (1)
7/10/2014
11
• Audio Formats are described by the sample rate and
quantization
• Voice quality: 8-bit quantization, 8000 Hz u-law
mono (8kBytes/s)
• 22 kHz 8-bit linear mono (22 kBytes/second) and
stereo (44 kBytes/s)
• CD quality 16-bit quantization, 44100 Hz linear
stereo (176.4 kBytes/s = 44100 samples x 16
bits/sample x 2 (two channels)/8000)
AUDIO FORMATS (2)
 Available formats on SUN
au - Sun File Format
wav - Microsoft RIFF/waveform Format
al - Raw A-law Data Format
u - Raw u-law Data Format
snd - NeXT File Format
 Available formats on Microsoft-Windows-based systems
( RIFF formats):
Waveform audio file format for digital audio hardware
MIDI file format for standard MIDI files
Audio Video Interleaved (AVI) Indeo file format
7/10/2014
12
AUDIO FORMATS (3)
• RIFF (Resource Interchange File Format) forms the
basis of a number of file formats. RIFF (similarly to
TIFF - Tagged Image File Format) is a tagged file
format. Tags allow applications capable of reading
RIFF files to read RIFF files by another application,
hence the word interchange in RIFF.
• Other Formats/Players - RealPlayer 7 (Windows
NT) with RealAudio, MP3 (MPEG Audio Layer 3)
audio, Midi players; MP3 players (MP3.com)
7/10/2014
13
VIDEO ENCODING (1)
7/10/2014
14
VIDEO (COLOR) ENCODING (2)
• During the scanning, a camera creates three
signals: RGB (red, greed and blue) signals.
• For compatibility with black-and-white video and
because of the fact that the three color signals are
highly correlated, a new set of signals of different
space are generated.
• The color systems correspond to the standards
such as NTSC, PAL, SECAM (conventional
systems).
7/10/2014
15
VIDEO ENCODING (3)
• For transmission of the visual signal we use three
signals: 1 luminance (brightness- basic signal) and
2 chrominance (color signals).
• In NTSC signal the luminance and chrominance
signals are interleaved;
• The goal at the receiver is : (1) separate luminance
from chrominance components, and (2) avoid
interference between them (cross-color, cross
luminance)
7/10/2014
16
VIDEO FORMAT (1)
 NTSC (National Television Systems Committee) TV
Format (USA TV Standard)
Analog video format
Color carrier 4.429 MHz; refresh rate 30 Hz (29.92Hz); 4.2 MHz for
luminance, 1.5 MHz for eac of the two chrominance channels
 Resolution: 833x635 picture elements
 Refresh Rate: 30 Hz
 Aspect Ratio: 4:3
 Interlaced format :
Each frame is composed of two consecutive fields, each containing
half the scanning lines of a picture, which are scanned and
presented in interlaced mode.
7/10/2014
17
VIDEO FORMATS (2)
 High Definition TV (HDTV)
Research on HDTV started in Japan 1968
Current TV standard
 Resolution:
twice as many horizontal and vertical columns and lines than
conventional systems (NTSC)
Two resolution systems
 High 1440 Level with 1,440x1,152 pixels
 High Level with 1,920x1,152 pixels
 Frame rate: 50 or 60 frames per second
 Aspect Ratio: 16:9
 Interlaced and/or progressive scanning formats
Conventional systems use interlaced (alternation of scanning lines)
format
HDTV similar to computer displays, uses progressive scanning
7/10/2014
18
SUMMARY
• Audio and Video Encoding principles are very
important, set the basis for digitization
• Different Digital Audio, Image and Video Formats,
not much standardization across
continents/countries, hence difficult to build
multimedia systems
• Multimedia systems are behind other systems such
as web systems, grid systems, operating systems,
…… due to the large space in audio and video
formats.
7/10/2014
19
SPECIAL ADDITIONALS
 Adobe Audition
 Magix Music Maker
 Media Player Classic
 PhotoDesk Pro Show
 Windows Media Player
 VLC Player
 AV Karaoke Maker
 Converters : flv to mp3 converter
7/10/2014
20
7/10/2014
21

Más contenido relacionado

La actualidad más candente

Digitization of Audio.ppt
Digitization of Audio.pptDigitization of Audio.ppt
Digitization of Audio.pptVideoguy
 
Audio compression 1
Audio compression 1Audio compression 1
Audio compression 1Rajat Kumar
 
Audio compression
Audio compressionAudio compression
Audio compressionSahil Garg
 
Audio compression
Audio compression Audio compression
Audio compression Darshan IT
 
Digital audio formats
Digital audio formatsDigital audio formats
Digital audio formatsamels_john
 
Digital Audio
Digital  AudioDigital  Audio
Digital Audiosurprisem
 
Introductory Lecture to Audio Signal Processing
Introductory Lecture to Audio Signal ProcessingIntroductory Lecture to Audio Signal Processing
Introductory Lecture to Audio Signal ProcessingAngelo Salatino
 
Speech Compression using LPC
Speech Compression using LPCSpeech Compression using LPC
Speech Compression using LPCDisha Modi
 
Mm01 a vformat
Mm01 a vformatMm01 a vformat
Mm01 a vformatgotovikas
 
Basics of audio coding
Basics of audio codingBasics of audio coding
Basics of audio codingsakshij91
 
Speech coding standards2
Speech coding standards2Speech coding standards2
Speech coding standards2elroy25
 
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications I
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications IDSP_FOEHU - Lec 13 - Digital Signal Processing Applications I
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications IAmr E. Mohamed
 
Digitizing and Delivering Audio and Video
Digitizing and Delivering Audio and VideoDigitizing and Delivering Audio and Video
Digitizing and Delivering Audio and VideoJenn Riley
 

La actualidad más candente (20)

Digitization of Audio.ppt
Digitization of Audio.pptDigitization of Audio.ppt
Digitization of Audio.ppt
 
3 Digital Audio
3 Digital Audio3 Digital Audio
3 Digital Audio
 
Audio compression 1
Audio compression 1Audio compression 1
Audio compression 1
 
Audio compression
Audio compressionAudio compression
Audio compression
 
Speech Compression
Speech CompressionSpeech Compression
Speech Compression
 
MPEG/Audio Compression
MPEG/Audio CompressionMPEG/Audio Compression
MPEG/Audio Compression
 
Audio compression
Audio compression Audio compression
Audio compression
 
Digital audio
Digital audioDigital audio
Digital audio
 
Digital audio formats
Digital audio formatsDigital audio formats
Digital audio formats
 
Audio compression
Audio compressionAudio compression
Audio compression
 
Digital Audio
Digital  AudioDigital  Audio
Digital Audio
 
Introductory Lecture to Audio Signal Processing
Introductory Lecture to Audio Signal ProcessingIntroductory Lecture to Audio Signal Processing
Introductory Lecture to Audio Signal Processing
 
Digital audio
Digital audioDigital audio
Digital audio
 
Speech Compression using LPC
Speech Compression using LPCSpeech Compression using LPC
Speech Compression using LPC
 
Mm01 a vformat
Mm01 a vformatMm01 a vformat
Mm01 a vformat
 
Basics of audio coding
Basics of audio codingBasics of audio coding
Basics of audio coding
 
Speech coding standards2
Speech coding standards2Speech coding standards2
Speech coding standards2
 
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications I
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications IDSP_FOEHU - Lec 13 - Digital Signal Processing Applications I
DSP_FOEHU - Lec 13 - Digital Signal Processing Applications I
 
Speech coding techniques
Speech coding techniquesSpeech coding techniques
Speech coding techniques
 
Digitizing and Delivering Audio and Video
Digitizing and Delivering Audio and VideoDigitizing and Delivering Audio and Video
Digitizing and Delivering Audio and Video
 

Similar a Multimedia Systems by Sahil Punni

Similar a Multimedia Systems by Sahil Punni (20)

simple video compression
simple video compression simple video compression
simple video compression
 
Analog to digital conversion
Analog to digital conversionAnalog to digital conversion
Analog to digital conversion
 
M1L1-2.ppt
M1L1-2.pptM1L1-2.ppt
M1L1-2.ppt
 
Audio-1
Audio-1Audio-1
Audio-1
 
Audio
AudioAudio
Audio
 
Mk3422222228
Mk3422222228Mk3422222228
Mk3422222228
 
Bb feb2005
Bb feb2005Bb feb2005
Bb feb2005
 
Digital Audio in Multimedia
Digital Audio in MultimediaDigital Audio in Multimedia
Digital Audio in Multimedia
 
Audio Essentials for Broadcast and Multiscreen
Audio Essentials for Broadcast and MultiscreenAudio Essentials for Broadcast and Multiscreen
Audio Essentials for Broadcast and Multiscreen
 
Digital Video And Compression
Digital Video And CompressionDigital Video And Compression
Digital Video And Compression
 
Multimedia and-system-design-sound-images by zubair yaseen& yameen shakir
Multimedia and-system-design-sound-images by zubair yaseen& yameen shakirMultimedia and-system-design-sound-images by zubair yaseen& yameen shakir
Multimedia and-system-design-sound-images by zubair yaseen& yameen shakir
 
SPEECH CODING
SPEECH CODINGSPEECH CODING
SPEECH CODING
 
Video
VideoVideo
Video
 
HDTV
HDTVHDTV
HDTV
 
multimedia chapter1
multimedia chapter1multimedia chapter1
multimedia chapter1
 
Unit 1 Lesson 01
Unit 1 Lesson 01Unit 1 Lesson 01
Unit 1 Lesson 01
 
Multimedia Design Chapter 4
Multimedia Design Chapter 4Multimedia Design Chapter 4
Multimedia Design Chapter 4
 
Beginning of dtv
Beginning of dtvBeginning of dtv
Beginning of dtv
 
05 capture
05 capture05 capture
05 capture
 
mpeg4copy-120428133000-phpapp01.ppt
mpeg4copy-120428133000-phpapp01.pptmpeg4copy-120428133000-phpapp01.ppt
mpeg4copy-120428133000-phpapp01.ppt
 

Último

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Steffen Staab
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsArshad QA
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...kellynguyen01
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...harshavardhanraghave
 
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...MyIntelliSource, Inc.
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVshikhaohhpro
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsJhone kinadey
 
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfLearn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfkalichargn70th171
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Modelsaagamshah0812
 
TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providermohitmore19
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfkalichargn70th171
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxbodapatigopi8531
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionSolGuruz
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...panagenda
 

Último (20)

CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICECHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview Questions
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
 
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTV
 
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS LiveVip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdfMicrosoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial Goals
 
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfLearn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Models
 
TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service provider
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptx
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with Precision
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
 

Multimedia Systems by Sahil Punni

  • 1. DIGITAL AUDIO AND VIDEO Sahil Punni 7/10/2014 1
  • 2. CONTENTS  Audio  How we hear Sound?  Basic Sound Concepts  Computer Representation of Audio  Audio Encoding  Audio Formats  Video Encoding  Video Formats  Conclusion  Additionals : Digital Audio and Video Editing Softwares Explained 7/10/2014 2
  • 3. AUDIO  Sound is a continuous wave that travels through the air.  The wave is made up of pressure differences. 7/10/2014 3
  • 4. HOW DO WE HEAR SOUND? 7/10/20144
  • 5. BASIC SOUND CONCEPTS  Frequency represents the number of periods in a second (measured in hertz, cycles/second)  Human hearing frequency range: 20 Hz - 20 kHz (audio), voice is about 500 Hz to 2 kHz.  Amplitude of a sound is the measure of displacement of the air pressure wave from its mean. 7/10/20145
  • 6. COMPUTER REPRESENTATION OF AUDIO • Speech is analog in nature and it is converted to digital form by an analog-to-digital converter (ADC). • A transducer converts pressure to voltage levels. • Convert analog signal into a digital stream by discrete sampling • Discretization both in time and amplitude (quantization) 7/10/2014 6
  • 7. AUDIO ENCODING (1) Audio Waves Converted to Digital • electrical voltage input • sample voltage levels at intervals to get a vector of values: (0, 0.2, 0.5, 1.1, 1.5, 2.3, 2.5, 3.1, 3.0, 2.4,...) • A computer measures the amplitude of the waveform at regular time intervals to produce a series of numbers (samples). • The ADC process is governed by various factors such as sample rate and quantization: binary number as output 7/10/2014 7
  • 8. AUDIO ENCODING (2) • Sampling Rate: rate at which a continuous wave is sampled (measured in Hertz) • Examples: CD standard - 44100 Hz, Telephone quality - 8000 Hz • The audio industry uses 5.0125 kHz, 11.025 kHz, 22.05 kHz, and 44.1 kHz as the standard sampling frequencies. These frequencies are supported by most sound cards. 7/10/2014 8
  • 9. AUDIO ENCODING (3)  The best-known technique for voice digitization is Pulse-Code Modulation (PCM).  Voice 4000 Hz What is the PCM sampling rate?  PCM provides analog samples which must be converted to digital representation. Each of these analog samples must be assigned a binary code. Each sample is approximated by being quantized as explained next. 7/10/2014 9
  • 10. AUDIO ENCODING (4)  Quantization (sample precision): the resolution of a sample value. Samples are typically stored as raw numbers (linear PCM format) or as logarithms (u-law or A-law) Quantization depends on the number of bits used measuring the height of the waveform Example: 16-bit CD quality quantization results in over 65536 values 7/10/2014 10
  • 11. AUDIO FORMATS (1) 7/10/2014 11 • Audio Formats are described by the sample rate and quantization • Voice quality: 8-bit quantization, 8000 Hz u-law mono (8kBytes/s) • 22 kHz 8-bit linear mono (22 kBytes/second) and stereo (44 kBytes/s) • CD quality 16-bit quantization, 44100 Hz linear stereo (176.4 kBytes/s = 44100 samples x 16 bits/sample x 2 (two channels)/8000)
  • 12. AUDIO FORMATS (2)  Available formats on SUN au - Sun File Format wav - Microsoft RIFF/waveform Format al - Raw A-law Data Format u - Raw u-law Data Format snd - NeXT File Format  Available formats on Microsoft-Windows-based systems ( RIFF formats): Waveform audio file format for digital audio hardware MIDI file format for standard MIDI files Audio Video Interleaved (AVI) Indeo file format 7/10/2014 12
  • 13. AUDIO FORMATS (3) • RIFF (Resource Interchange File Format) forms the basis of a number of file formats. RIFF (similarly to TIFF - Tagged Image File Format) is a tagged file format. Tags allow applications capable of reading RIFF files to read RIFF files by another application, hence the word interchange in RIFF. • Other Formats/Players - RealPlayer 7 (Windows NT) with RealAudio, MP3 (MPEG Audio Layer 3) audio, Midi players; MP3 players (MP3.com) 7/10/2014 13
  • 15. VIDEO (COLOR) ENCODING (2) • During the scanning, a camera creates three signals: RGB (red, greed and blue) signals. • For compatibility with black-and-white video and because of the fact that the three color signals are highly correlated, a new set of signals of different space are generated. • The color systems correspond to the standards such as NTSC, PAL, SECAM (conventional systems). 7/10/2014 15
  • 16. VIDEO ENCODING (3) • For transmission of the visual signal we use three signals: 1 luminance (brightness- basic signal) and 2 chrominance (color signals). • In NTSC signal the luminance and chrominance signals are interleaved; • The goal at the receiver is : (1) separate luminance from chrominance components, and (2) avoid interference between them (cross-color, cross luminance) 7/10/2014 16
  • 17. VIDEO FORMAT (1)  NTSC (National Television Systems Committee) TV Format (USA TV Standard) Analog video format Color carrier 4.429 MHz; refresh rate 30 Hz (29.92Hz); 4.2 MHz for luminance, 1.5 MHz for eac of the two chrominance channels  Resolution: 833x635 picture elements  Refresh Rate: 30 Hz  Aspect Ratio: 4:3  Interlaced format : Each frame is composed of two consecutive fields, each containing half the scanning lines of a picture, which are scanned and presented in interlaced mode. 7/10/2014 17
  • 18. VIDEO FORMATS (2)  High Definition TV (HDTV) Research on HDTV started in Japan 1968 Current TV standard  Resolution: twice as many horizontal and vertical columns and lines than conventional systems (NTSC) Two resolution systems  High 1440 Level with 1,440x1,152 pixels  High Level with 1,920x1,152 pixels  Frame rate: 50 or 60 frames per second  Aspect Ratio: 16:9  Interlaced and/or progressive scanning formats Conventional systems use interlaced (alternation of scanning lines) format HDTV similar to computer displays, uses progressive scanning 7/10/2014 18
  • 19. SUMMARY • Audio and Video Encoding principles are very important, set the basis for digitization • Different Digital Audio, Image and Video Formats, not much standardization across continents/countries, hence difficult to build multimedia systems • Multimedia systems are behind other systems such as web systems, grid systems, operating systems, …… due to the large space in audio and video formats. 7/10/2014 19
  • 20. SPECIAL ADDITIONALS  Adobe Audition  Magix Music Maker  Media Player Classic  PhotoDesk Pro Show  Windows Media Player  VLC Player  AV Karaoke Maker  Converters : flv to mp3 converter 7/10/2014 20

Notas del editor

  1. Sound is detected by measuring the pressure level at a point When an acoustic signal reaches the otter- ear (Pinna), the generated wave will be transformed into energy and filtered through the middle-ear. The inner-ear (Cochlea) transforms the energy into nerve activity. In similar way, when an acoustic wave strikes a microphone, the microphone generates an electrical signal, representing the sound amplitude as a function of time.
  2. If voice data are limited to 4000 Hz, then PCM samples 8000 samples/second which is sufficient for the input voice signal.