|
Dear All, Please forward the following PhD studentship information to anyone who may be interested in applying. The Acoustics Research Centre at Salford has several areas
of interest which overlap with those on Auditory. Applications are invited from UK and EU candidates for fully-funded PhD studentships at the University of Salford. TOPICS The Acoustics Research Centre within the School of Computing, Science and Engineering is keen to encourage high-quality applications on the following topics: 1.
Modelling expectation in soundscapes. Supervisor: Professor Bill Davies (w.davies@xxxxxxxxxxxxx) Human response to complex acoustic scenes is a major topic of research at Salford. We have previously shown (Bruce and Davies, 2014)
that listener expectation has a significant effect on evaluation of outdoor urban soundscapes. We have since extended our soundscape work to show that similar strategies are used by listeners with complex spatial audio scenes (Woodcock et al., 2016; 2017).
We are now applying our models and methods to inform machine listening systems for processing the torrent of everyday audio in networked computer systems (Bones et al., 2016). There is a gap in our work (and that of other researchers) when it comes to expectation. We know it’s important, but we don’t have
a model for it. The goal of this PhD will be to develop a model for how listener expectation influences evaluation of (non-speech, non-music) soundscapes. Simple models exist for music expectation and these will be a likely starting point for this PhD. References Bones, O., W. J. Davies and T. J. Cox (2016). An evidence-based taxonomy of everyday sounds. Acoustical Society of America. Hawaii. Bruce, N. S. and W. J. Davies (2014). "The effects of expectation on the perception of soundscapes." Applied Acoustics 85: 1-11. Woodcock, J., W. J. Davies, T. J. Cox and F. Melchior (2016). "Categorization of broadcast audio objects in complex auditory scenes."
J. Audio Eng. Soc. 64: 380-394. Woodcock, J., W. J. Davies and T. J. Cox (2017). "A cognitive framework for the categorisation of auditory objects in urban soundscapes."
Applied Acoustics 121: 56-64. 2.
Structure and scale in soundscape cognition. Supervisor: Professor Bill Davies (w.davies@xxxxxxxxxxxxx) Human response to soundscapes is a major topic of research at Salford. Soundscape research has many results on the characteristics
of whole soundscapes (e.g. Davies et al., 2013), some on individual sounds (e.g. Bones et al., 2016), and a few on the characteristics of one sound. But there is not enough evidence of how these mental representations are tied together in an overall cognitive
structure. The goal of this project is to explore the interactions between auditory attention, physical scale and cognitive scale in complex acoustic scenes. We have previously suggested (Davies, 2015) the concept of the scale of the cognitive structure is
a fundamental feature that underlies many of the important attributes in the perception of soundscapes, spatial audio and music. The goal of this PhD will be to develop a model of cognitive scale for soundscape perception. References Bones, O., W. J. Davies and T. J. Cox (2016). An evidence-based taxonomy of everyday sounds. Acoustical Society of America. Hawaii. Davies, W. J., M. D. Adams, N. S. Bruce, M. Marselle, R. Cain, P. Jennings, J. Poxon, A. Carlyle, P. Cusack, D. A. Hall, A. Irwin,
K. I. Hume and C. J. Plack (2013). "Perception of soundscapes: An interdisciplinary approach." Applied Acoustics 74(2): 224-231. Davies, W. J. (2015). Cognition of soundscapes and other complex acoustic scenes. Internoise 2015. San Francisco.
3.
Unintelligible radio dramas Supervisor: Professor Trevor Cox (t.j.cox@xxxxxxxxxxxxx) Complaints about unintelligible speech on TV drama is becoming a common complaint, with recent examples including Jamaica Inn, Poldark
and SS-GB. Speech intelligibility research has traditionally focussed on transmission problems, but the recent examples demonstrate some problems are caused by mumbling and whispering by actors. In this project you will apply psychoacoustic testing to better
understand the requirements of listeners. You will apply statistics and machine learning (e.g. deep nets) to model the effects of accents and poor elocution. From there, you will produce meters than can be used by sound engineers to monitor the intelligibility
of dialogue and so improve TV sound. 4.
Computational Model of Situational Awareness for users of smartphones in the vicinity of traffic Supervisor: Dr Bruno Fazenda (b.m.fazenda@xxxxxxxxxxxxx) Advances in technology (Bluetooth headsets, ‘iPods’, quieter cars, helmets) are leading to situations where an individual's perception
of the surrounding environment is hindered, making him/her more vulnerable to accidents and/or intentional dangers. Examples include: a driver unaware of a fast moving emergency vehicle; a motorbike or cyclist wearing a protection helmet; a civil protection
foraging robot or vehicle on patrol. This project aims to investigate this problem from both a human factors as well as technological development points of view. A candidate reading for a PhD in this area will be designing experiments in our fully immersive
3D audiovisual environment in order to collect behaviour data that can help us understand impairments caused by the use of portable infotainment technology. The goal of the project is to develop detection and warning systems that can use sensor and usage data
from devices, allowing constant monitoring of behaviour and environment and subsequently model drops in attention and awareness. This PhD may include all or some of the following multi-disciplinary skills: sensor engineering (with particular emphasis on acoustic
detection), digital signal processing; cognitive behaviour. There is an opportunity to be involved in a funded international collaboration through the Royal Society.
The goal of this PhD will be to develop prediction models of awareness in users. 5.
Auditory Perception in Virtual and Augmented Reality Spaces Supervisor: Dr Bruno Fazenda (b.m.fazenda@xxxxxxxxxxxxx)
Headphones are ubiquitous and a very convenient way of reproducing sound. More recently attention has been devoted to full surround
sound capabilities over headphones and a great deal of research effort is being devoted to this, particularly in areas of Virtual and Augmented Reality. However, convincing rendition of acoustic spaces with headphones is still elusive and problems still exist
with internalisation, individualisation, acoustic modelling of the spaces, etc. This PhD project takes at look at the issue from a more holistic perspective. The multimodal aspects of audio and visual interactions are to be considered as well as important
human factors such as personality and cognitive styles and how these affect perception of virtual and augmented spaces. The project will involve the design of subjective experiments to be undertaken in virtual or augmented reality spaces and will include
both aspects of signal processing and room acoustics modelling as well as applied psychology methods. 6.
Personalised Music Creation and Distribution using Object Based Audio Supervisor: Dr Bruno Fazenda (b.m.fazenda@xxxxxxxxxxxxx)
Music creation and consumption has followed the same paradigm since the advent of recording. Hours of composition, recording and mixing
result in a linear piece which the listener consumes repeatedly. Music consumption progressed from physical formats to internet streaming and subscription services which ‘learn’ consumer tastes. This has given rise to playlists and algorithms providing content
delivery which can be mediated by listener goals such as ‘music to go to sleep’ or ‘drive music’. However, these services simply aid the delivery of existing music items, rather than facilitate the creation of optimised, personalised content.
This project will apply a new paradigm for music creation and consumption to deliver new music content personalised to listener context,
different every time it is consumed, and directly aligned to listener wellbeing goal. It will deliver a framework of music composition and consumption that senses listener state and context using wearables and smartphone sensors, through which the composer
will be able to dynamically ‘perform’ their music. It will enable novel creative, performative possibilities for the artist and a new form of music experience and service delivery for the listener. For the artist, the proposed framework will facilitate capture
of ideas and associated rights and provide a 'fair ecosystem' when content is reused or redistributed. For listeners it will form a novel experience delivery acknowledging principles of embodied cognition: that our thought-processes and our resulting wellbeing
states are tied to, and influenced by, our immediate environment and our interactions with it.
The project will involve research into aspects of object based audio, music and wellbeing, generative music composition paradigms and
automatic mixing methods. It will involve perceptual testing in both lab and field conditions through applications deployed on smartphones. You will collaborate with musicians and audio technologists. 7.
Automatic Detection of Audio Quality in Commercial Music Productions Supervisor: Dr Bruno Fazenda (b.m.fazenda@xxxxxxxxxxxxx)
Some music productions sound great and some don’t: the sound quality of audio programme material is very variable. Expert and naïve
listeners are quite good at picking up these differences in sound quality. However, so far there are no metrics that can quantify if a given music track is of good quality or not. This project aims to define and extract quality features from audio signals
that enable an automated rating of the acoustic quality therein. With the recent advances in deep learning networks, it is possible to predict whether a given musical piece has elements of high quality
but the technical rules that afford that quality are hidden. This project will use the recent advances in signal processing and data mining to support a substantial study of human factors that determine perceived quality in sound and audio production. The
foreseen outcomes are: 1) A framework that sets the relative importance of various objective acoustic measures of signal content in the context of human listening; 2) A digital tool that automatically rates and improves audio quality in a given stream. Applications
of the knowledge and technology span from automated adjustment to different reproduction scenarios (eg: radio speech in a car vs. live sound) to archive recovery.
QUALIFICATIONS Applicants should have a good undergraduate honours degree (1st or 2:1) and/or a good MSc degree in acoustics, psychology, electronic engineering or
a related subject. Desirable experience includes design of listening tests, statistical analysis, programming (e.g. MATLAB), and scientific publication.
ENVIRONMENT You can expect to be able to take advantage of our world-class experimental facilities including anechoic and semi-anechoic chambers, listening room, object-based
spatial audio systems, head-tracked binaural system, and so on, as appropriate. You’ll join a thriving Acoustics Research Centre and will work alongside PhD students, post-doctoral fellows and senior researchers who are researching related topics (http://www.salford.ac.uk/computing-science-engineering/research/acoustics).
The topic and methods of each project might be varied to suit the strengths of the applicant. FUNDING Successful candidates will receive a bursary of £14,553 tax free for up to three years and will also get their tuition fees paid. TO APPLY You are strongly encouraged to contact the likely supervisor indicated above for an informal discussion before you apply. Competition for these fully-funded places
is expected to be intense and you will benefit from our advice on your application. Further details and application form can be found at
http://www.salford.ac.uk/study/postgraduate/fees-and-funding/funded-phd-studentship Best, Bill Davies Professor Bill Davies Associate Dean Academic | School of Computing, Science and Engineering Room 108, Newton Building, University of Salford, Salford M5 4WT t: +44 (0) 161 295 5986 w.davies@xxxxxxxxxxxxx |
www.salford.ac.uk |