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Automated quality analysis of telecommunications audio


Project Description

A fully funded PhD scholarship is available with the Human-in-the-Loop Analytics (HiLA) program at Monash University, Melbourne, Australia. https://www.monash.edu/graduate-research/partnerships/hila-grip

HiLA is a Graduate Research Industry Partnership (GRIP) that has been established to allow Monash University and its Industry partners to collaborate on common research objectives.
https://www.monash.edu/graduate-research/partnerships/grip
With the support of Monash’ partners, HiLA PhD scholarships are provided with significant benefits beyond other scholarships on offer. These benefits include:

A fully funded PhD scholarship with Monash University that is available for domestic (Australian) and international students. The 3 to 3.5 year award covers all course fees and a $30,000 AUD per year tax-free stipend;
An internship with the Industry partner - where PhD candidates will spend a portion of their candidature located on site and being supported by the partner;
Access to real world problems supported by real world data;
Where the industry partner is located overseas or interstate, travel and accommodation (when working on site with the partner);
Travel and incidental support for conferences;
Enrollment in the HiLA professional development program;

All HiLA PhD scholarships will commence in Semester 2, 2019.

SUPERVISION:
The successful candidate will be supervised by Professor Jon McCormack from the Faculty of Information Technology.

PROJECT DETAILS:
The specific project centers around the following research opportunity:

This project will explore the application of machine learning approaches with pre-labelled audio files, unlabelled audio and data-augmentation techniques to quickly and accurately assess the quality of audio and classify distortion characteristics. The candidate will research novel machine learning approaches with a methodology based on iterative experimentation through model development, implementation in software and testing with automated tools and user feedback.

Mean opinion score (MOS) is a measure used in telecommunications to measure the quality of audio (or video) in a system on a 5-point rating scale where 1 is bad (unintelligible) and 5 is excellent. These ratings are usually gathered in a subjective quality evaluation test or the use of algorithms such as PSQM, PESQ, and POLQA. Enhancing this process through efficient machine learning algorithms has direct applicability in telecommunications and poses interesting research questions around automated data labelling, time-series classification and signal processing.

This project will also look at Identifying characteristic distortions that contribute to reduced MOS scores such as gaps and muffled audio caused by transcoders and accurately labelling these distortions temporally in audio streams.

As a Graduate Research Industry Partnership project, the candidate will have access to knowledge and resources from Monash University and Cyara, including state-of-the-art machine learning hardware (NVIDIA DGX-1) and access to large scale proprietary datasets. It also provides the opportunity for research to be tested and implemented in solving real-world problems during the project cycle.

This project would suit a candidate with a background in machine learning, especially in the areas of audio analysis and digital signal processing. Experience with deep learning frameworks such as PyTorch, Tensorflow or Caffe is desirable, but not required.

APPLICATION PROCESS
Candidates must fill out the online to Request to Apply form, which can be found at:

https://docs.google.com/forms/d/e/1FAIpQLSdUiAswykQg43s8qIoLfq1eKfiGCZrgnkeoT7IQXOlhdJ8TIg/viewform

Please make sure you indicate that the PhD Topic is “Automated quality analysis of telecommunications audio”;

In addition to filling out the form, a copy of your academic transcripts and CV should be emailed to .

Applicants must possess a Bachelor’s or equivalent degree with first-class Honours, and/or a distinction in a research Masters degree with relevant experience (e.g., data analysis, artificial intelligence, social informatics, psychology, human-computer interaction or data visualisation). Review of applications will begin immediately and short-listed candidates will be contacted for more information and invited to interview. The successful candidate will be invited to apply to Monash with the deadline for applications being the 31st May 2018.

International students that can demonstrate English proficiency are encouraged to apply.

Funding Notes

A fully funded PhD scholarship with Monash University that is available for domestic (Australian) and international students. The 3 to 3.5 year award covers all course fees and a $30,000 AUD per year tax-free stipend;

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