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Unit of study_

DESC9115: Digital Audio Systems

Semester 1, 2021 [Normal day] - Camperdown/Darlington, Sydney

The objective of this unit is to provide both a strong theoretical understanding of digital audio and practical experience in applying these principles to digital audio systems. This unit offers a systematic approach to understanding digital audio systems. Beginning with basic principles the unit provides a knowledge base for understanding advanced digital audio components, systems and techniques. Examples of everyday audio signals are used and characterised in terms of their temporal and spectral properties. Practical application is emphasised and is supported through laboratory exercises that include programming as well as the use of current hardware and software packages. Topics include: principles of digital signals and systems, sampling and quantisation, convolution, discrete Fourier transform (DFT), z-transform, transfer functions and impulse responses, finite and infinite impulse responses filtering, audio system design, time-variant systems, audio data compression and real-time audio DSP. Having successfully completed this unit the student will have the tools to understand what happens to a digital audio signal when a given process is applied to it; how to best apply this process and how to successfully combine digital audio components.

Unit details and rules

Unit code DESC9115
Academic unit Architectural and Design Science
Credit points 6
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Densil Cabrera,
Lecturer(s) Ella Manor,
Type Description Weight Due Length
Skills-based evaluation Lab exercises
Programming exercises
20% Multiple weeks n/a
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment Assignment 1
Written and non-written elements
30% Week 07
Due date: 21 Apr 2021 at 23:00
A set of exercises
Outcomes assessed: LO1 LO2 LO3
Assignment Assignment 2
Written and design elements
50% Week 13
Due date: 02 Jun 2021 at 23:00
1500 words report, MATLAB project
Outcomes assessed: LO1 LO2 LO3 LO4 LO6

Assessment summary

Assignment 1 – Students will be required to complete a set of exercises consisted of questions that draw on materials from lectures and tutorials. Students will be required to use MATLAB to complete some of the exercises.

Assignment 2 – Students will be required to submit a user-friendly digital audio system of their choice programmed in MATLAB, including demo examples and a written review consisted of a literature report of the topic and a detailed description of their own work.

Lab exercises – the focus is primarily on solving simple audio DSP problems using the MATLAB software. One-on-one assistance will be available during the lab sessions in the second half of each class meeting.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100

Work of outstanding quality, demonstrating mastery of the learning outcomes assessed. The work shows significant innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or exceptional skill.


75 - 84

Work of excellent quality, demonstrating a sound grasp of the learning outcomes assessed. The work shows innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or superior skill.


65 - 74

Work of good quality, demonstrating more than satisfactory achievement of the learning outcomes assessed, or work of excellent quality for a majority of the learning outcomes assessed.


50 - 64

Work demonstrating satisfactory achievement of the learning outcomes assessed.


0 - 49

Work that does not demonstrate satisfactory achievement of one or more of the learning outcomes assessed.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to digital audio systems and signals Lecture (1.5 hr) LO1
Introduction to MATLAB Computer laboratory (1.5 hr) LO1
Week 02 Introduction to sampling theory Lecture (1.5 hr) LO1
Audio signal sampling decimation Computer laboratory (1.5 hr) LO1
Week 03 Introduction to Digital Signal Processing (DSP) Lecture (1.5 hr) LO1 LO4
DSP in MATLAB Computer laboratory (1.5 hr) LO1 LO4
Week 04 Convolution Lecture (1.5 hr) LO1 LO2 LO4
Simple reverb simulation Computer laboratory (1.5 hr) LO1 LO2 LO4
Week 05 Discrete Fourier Transform (DFT) Lecture (1.5 hr) LO1 LO2 LO4
DFT and time segment processing Computer laboratory (1.5 hr) LO1 LO2 LO4
Week 06 Intro to the Z-Transform and Transfer functions and impulse responses Lecture (1.5 hr) LO1 LO2 LO3 LO4
HRTF and HRIR Computer laboratory (1.5 hr) LO1 LO2 LO4
Week 07 Finite-Impulse-Response (FIR) filters Lecture (1.5 hr) LO1 LO3 LO4
FIR filters and window functions Computer laboratory (1.5 hr) LO1 LO3 LO4
Week 08 Infinite-Impulse-Response (IIR) filters Lecture (1.5 hr) LO1 LO3 LO4
Combining FIR and IIR filters to create artificial reverb Computer laboratory (1.5 hr) LO1 LO3 LO4
Week 09 Audio system design and sampling of musical instrument sound Lecture (1.5 hr) LO1 LO4 LO6
LPC analysis and resynthesis Computer laboratory (1.5 hr) LO1 LO4 LO6
Week 10 Time-variant systems Lecture (1.5 hr) LO1 LO4 LO6
Time delay modulation-based effects Computer laboratory (1.5 hr) LO1 LO4 LO6
Week 11 Audio data compression techniques Lecture (1.5 hr) LO1 LO4 LO5 LO6
Audio data compression in MATLAB using DCT Computer laboratory (1.5 hr) LO1 LO4 LO5 LO6
Week 12 Real-time audio DSP Lecture (1.5 hr) LO1 LO4 LO6
Introduction to audio DSP in Max/MSP Computer laboratory (1.5 hr) LO1 LO4 LO6
Week 13 Guest lecture Lecture (3 hr) LO1 LO2 LO3 LO4 LO5 LO6

Attendance and class requirements

Please refer to the Resolutions of the University School:

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Reading and electronic sources are accessible online or via the library’s website

Smith, S. W. (1999). The Scientist and Engineer's Guide to Digital Signal Processing(2nd ed.). Retrieved from

Rao, K. D. (2018). Digital Signal Processing Theory and Practice. Singapore: Springer Singapore.

Hill, P. (2018). Audio and Speech Processing with MATLAB: CRC Press.

Zölzer, U. (2011). Dafx: Digital Audio Effects (2nd ed.): John Wiley & Sons.

Pohlmann KC. (1989) Principles of digital audio. Sams; 1989.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. use the terminology associated with the digital sampling, processing, and reconstruction of analog audio signals. Demonstrate a basic knowledge of Sampling Theory, including audio signal sampling-rate conversion, and be able to argue for the suitability of particular solutions for storage and distribution of audio signals. Demonstrate knowledge of human auditory perception in the contexts of audio system design and Digital Signal Processing (DSP)
  • LO2. understand and be able to apply the Discrete Fourier Transform to time domain signals to determine their frequency composition. Demonstrate knowledge of Convolution and be able to correctly derive Transfer Functions and Impulse Responses from the analysis of audio systems
  • LO3. understand audio system design, and particularly two types of digital filters: the Finite-Impulse-Response (FIR) filter and the Infinite-Impulse-Response (IIR) filter
  • LO4. understand the analysis and design of Linear Time-invariant Systems related to the simulation of sound propagation through space
  • LO5. understand modern forms of audio data compression and demonstrate knowledge of advanced audio coding algorithms for storage and distribution of audio content
  • LO6. show familiarity with new areas of work involving digital audio systems, particularly in advanced applications development.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Lecturer and Tutor: Ella Manor


Lectures: Wed 18:00 – 19:30, Wilkinson Seminar Room 231 (Arch SR 3)

Tutorials: Wed 19:30 – 21:00, Wilkinson 262 Computing Studio

Consultation hours: Wednesdays 15:00-17:00 (by scheduled appointment)

Additional costs

There are no additional costs for this unit.

Site visit guidelines

There are no site visit guidelines for this unit.

Work, health and safety

There are no specific work health and safety requirements for this unit.


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