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CMPE3I07 - SOUND AND IMAGE II

Module Code:
CMPE3I07
Department:
Computing Sciences
Credit Value:
20
Level:
3
Organiser:
Dr. Barry Theobald
This module continues the exploration of computer processing of sound and image signals begun in Sound and Image I. In the “sound” component, we focus on speech processing, a technology that has already had a huge impact and holds great promise for the future. We cover: 1) speech-coding, which enables us to understand how one of the most significant technologies of recent times (the mobile telephone) is able to transmit speech at a low data-rate; 2) speech recognition, which is now becoming commonplace in interactive voice systems; and 3) speech synthesis. In the “image” component, we focus on the analysis of image signals and learn how to apply advanced filtering and enhancement techniques to images to restore them, and the basics of computer vision systems. These concepts are re-enforced with practical coursework, which gives students hands-on experience of processing audio and video signals.

In lectures, handouts will be distributed for material that is difficult or lengthy to copy from the board e.g. derivations of formulae. These handouts will be available on Blackboard. However, the handouts are not comprehensive, and students are expected to make their own notes from lecturers' notes on the board. In workshops, students will be expected to tackle problems individually but with help available from the seminar leader and one other teacher. For some workshops, the class will read sections of a textbook beforehand and then analyse the material in the workshop. Laboratory work (MATLAB programming) will take place during time-tabled laboratory periods using networked personal computers. CMP teaching laboratories running MATLAB are available to CMP students during term time outside time-tabled teaching hours.


Required purchases

  • W. and J. Holmes, Speech Synthesis and Recognition,CRC
  • R. Gonzalez, and R. Woods, Digital Image Processing Prentice Hall

Possible alternative purchases:

Gonzalez, R. and Woods,R., Digital Image Processing Prentice Hall,


Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including    the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be investigated. Possible consequences of plagiarism include deduction of marks and disciplinary action, as detailed by UEA's Policy on Plagiarism and Collusion.


Module specific:

  • Understanding of the effects of a sampled representation of a continuous signal
  • Knowledge of the processes involved in speech production and the fundamentals of articulatory and acoustic phonetics
  • Understanding and analysis of the source-filter model of speech production and how it is applied in speech coding
  • An overview of the processes involved in speech recognition, appreciation of the problems that underlie each and an appreciation of how stochastic modelling can be used
  • Appreciation of the different approaches to speech synthesis and the advantages and disadvantages of each
  • Understanding of signal representation in the frequency domain
  • Understanding of frequency domain analysis for multi-dimensional signal
  • Understanding of image filtering techniques
  • Understanding of the differences between enhancement methods and restoration methods
  • Understanding of frequency domain techniques for image restoration

Transferable skills:


  • Enhanced MATLAB programming skills
  • Skills in the manipulation of sound and image files
  • Enhanced problem-solving skills
  • Increased knowledge and appreciation of speech and language


 


Subject specific:

  • In-depth understanding of DSP and its application
  • Ability to design discrete-time filters and process signals with them
  • Ability to use DSP techniques to process audio and video signals for use in audio and video coding and recognition systems
  • Understanding of the important areas in image and speech technology and of the research issues in them

Total hours: 49

Lectures:  22, hours: 1, Content (with provisional weekly schedule)

  1. Introduction to module; Introduction to the speech signal
  2. Source/filter model of speech production I 
  3. Source/filter model of speech production II 
  4. Speech recognition: the front end 
  5. Speech recognition: stochastic methods and search methods 
  6. Speech recognition; acoustic and language modelling 
  7. Speech synthesis I 
  8. Speech synthesis II 
  9. Speech dialogue systems 
  10. Speech Coding
  11. Vectors and Review of Complex Numbers
  12. Complex Exponential Representation of Signals
  13. Complex Fourier Series
  14. Introduction to the DFT
  15. Frequency Domain Filtering
  16. Frequency Domain Filter Design
  17. Image Restoration
  18. Wiener Filtering
  19. Audiovisual Speech
  20. Audiovisual Speech Synthesis
  21. Revision I
  22. Revision II


Workshops: 10, hours: 15, Content (with provisional weekly schedule)

  1. Assignment I briefing 
  2. Speech coding 
  3. Speech recognition I 
  4. Speech recognition II
  5. Speech synthesis
  6. Complex Exponentials
  7. Discrete Fourier Transforms 
  8. Assignment II Briefing 
  9. Frequency Domain Filtering
  10. Filter Design

Laboratory Work: 12, hours: 12, Content (with provisional weekly schedule)

  1. Front-end speech processing 
  2. Speech Coding 
  3. Vowel recognition
  4. Image processing 1 
  5. Introduction to the DFT
  6. Image Restoration


 


Coursework