Measuring and characterising nonlinear responses of television audio chains
Location: McMahons Point, Sydney, NSW
Duration: 5-6 months
Proposed start date: February 2018
Keywords: Signal processing, Matlab, Scripting, audio, System identification, nonlinear signal processing
The audio system on a television often pushes the boundaries of the capabilities of what small speakers can do. In order to obtain acceptable sound, the audio signal chain on a television will often incorporate limiters, automatic gain control, and other nonlinear signal processing components. If the audio output of a TV is going to be used as part of a communication system, then these nonlinear responses destroy echo cancellation.
Dolby is interested in measuring and modelling the non-linear characteristics of this audio chain. We will be able to drive the input audio and to measure the output of the speakers, but the processing chain is essentially a black box. This modelling should be considered as a system identification of a nonlinear system.
Research to be Conducted
- Probe and characterise a set of televisions to investigate the nonlinear responses of the audio systems of televisions
- This involves developing diagnostic signal techniques that perform a System Identification of a black box non linear system (TV audio chain)
- This incorporates data collection on a large set of televisions that will involve developing and scripting a data collection system
- Work with other researchers to incorporate the nonlinear responses into an echo management system that linearises the television audio chain
- The resources required to complete this project (all to be supplied by Dolby) are:
- A range of televisions to test
- Multi-channel audio playout and capture systems.
- Software tools to develop the analysis.
- A PC with Matlab and appropriate software tools.
- Work pattern: Standard 38-hour week (including time for the intern to visit their Academic Mentor)
- It is expected that the intern will mostly work on-site in the Dolby office
- Supervision will be carried out by the Senior Manager, Sound Technology Platform Development
For this project, we are looking for PhD students with:
- Digital Signal processing knowledge
- Data analysis
- Ability to synthesize knowledge contained in technical literature into useful recommendations for the project
- A high-level of mathematical fluency
- A report describing an analysis of the nonlinear characteristics of a set of television sets
- A portable measurement rig.
- Diagnostic signals and analysis scripts that can be used to analyse the nonlinear response of a television in a single test suite.
This project will offer the intern a number of opportunities for on-the-job development. Opportunities include:
- Working in a cross-functional research team
- Learning from experienced audio researchers, software engineers, DSP engineers, electro-acoustics engineers and audio experts
- Using sophisticated data collection systems
- Contributing to a commercial project
The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.
It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80-90% of their time on-site with the industry partner. The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
To participate in the APR.Intern program, all applicants must satisfy the following criteria:
- Be a PhD student currently enrolled at an Australian University.
- PhD candidature must be confirmed.
- Applicants must have the written approval of their Principal Supervisor to undertake the internship. This approval must be submitted at the time of application.
Internships are also subject to any requirements stipulated by the student’s and the academic mentor’s university.
25 February 2018
INT – 0375