PhD Position in Adaptive Deep Learning for Speech and Language

The LivePerson Centre for Speech and Language offers a 3 year fully funded PhD studentship
covering standard maintenance, fees and travel support, to work on deep neural network adaptive
learning modules for speech and language. The Centre is connected with the Speech and Hearing
(SpandH) and the Natural Language Processing (NLP) research groups at the Department of
Computer Science at the University of Sheffield.

Domain mismatch remains a key issue for speech and language technologies for which traditional
solutions are transfer learning and adaptation. The latter was widely used for modelling of speech in
the context of generative models, however less so with modern neural network approaches. Such
adaptation targeted features or models and was often informed by previous model output and
estimates of latent factors. These approaches were often informed by observations on human abilities
to adapt and adjust to new acoustic or semantic situations. Adaptation in neural networks is model
based and often implicit - through attention or dynamic convolution. However, these methods to date
still fail to reproduce the rapid learning and adaptation that humans exhibit when being exposed to new
contexts.

The objective in this project is to conduct research into neural network structures that are capable of
rapidly adjusting to a change in latent factors and at the same time allow for robust control. This will
require rapid feedback mechanisms on the mismatch between the observed data and the model
expectation. A range of strategies may be applied - through instantaneous feedback or through control
of transformational model parameters. All proposals are to be implemented and tested on speech, and
where suitable, also language data. Experiments should be conducted on a range of tasks of different
complexity in the context of different data types.

The student will join a world-leading team of researchers in speech and language technology. The
LivePerson Centre for Speech and Language Technology was established in 2017 with the aim to
conduct research into novel methods for speech recognition and general speech processing, including
end-to-end modelling, direct waveform modelling and new approaches to modelling of acoustics and
language. It has recently extended its research remit to spoken and written dialogue. The Centre hosts
several Research Associates, PhD researchers, graduate and undergraduate project students,
Researchers and Engineers from LivePerson, and academic visitors. Being fully connected with
SpandH brings collaboration, and access to a wide range of academic research and opportunities for
collaboration inside and outside of the University. The Centre has access to extensive dedicated
computing resources (GPU, large storage) and local storage of over 60TB of raw speech data.

The successful applicant will work under the supervision of Prof. Hain who is the Director of the
LivePerson Centre and also Head of the SpandH research group. SpandH was and is involved in a
large number of national and international projects funded by national bodies and EU sources as well
as industry. Prof. Hain also leads the UKRI Centre for Doctoral Training In Speech and Language
Technologies and their Applications (https://slt-cdt.ac.uk/) - a collaboration between the NLP research
group and SpandH. Jointly, NLP and SpandH host more than 110 active researchers in these fields.

This project will start as soon as possible.

How to Apply:

All applications must be made directly to the University of Sheffield using the

Postgraduate Online Application Form.

Information on what documents are required and a link to the application form can
be found here - https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
On your application, please name Prof. Thomas Hain as your proposed supervisor
and include the title of the studentship you wish to apply for.
Your research proposal should:

• Be no longer than 4 A4 pages, including references
• Outline your reasons for applying for this studentship
• Explain how you would approach the research, including details of your
• skills and experience in the topic area

If you have any queries, please contact phd-compsci@sheffield.ac.uk

Funding:

This position is fully funded by LivePerson, covering all tuition fees and a stipend at
the standard UKRI rate.