Research Associate in Integrated Multitask Neural Speech Labell

Profile

Research Associate in Integrated Multitask Neural Speech Labelling
University of Sheffield
- Department of Computer Science
Location:
Sheffield
Salary:
£35,333 to £43,414
Hours:
Full Time
Contract Type:
Fixed-Term/Contract
Placed On:
12th June 2023
Closes:
30th June 2023
Job Ref:
UOS037516
We are seeking an outstanding Research Associate to work on Integrated Multitask Neural Speech Labelling at the LivePerson Centre for Speech and Language Technology based at **MEMBERS ONLY**SIGN UP NOW***.. The Centre is linked with the Speech and Hearing (SPandH) research group in the Department of Computer Science.
This world-leading team of researchers focus on speech and language technology. Working on new ways to integrate a variety of speech technology labelling, clustering or segmentation
tasks into a single algorithm or process, in the context of deep neural networks
. Even end to end (E2E) automatic speech recognition
is typically considered as a standalone process, independent of other speech audio technology tasks such as diarisation, acoustic event detection or intent recognition
. There is recent interest in integration of a range of speech technology systems, enabled by the commonality of deep learning structures. Several solutions to specific problems have been proposed. Such strategies involve fusion of input streams at different levels, parallel multi-stream recognisers, or simply label prefixing. The objective in this project is to explore and analyse the benefit of different strategies and find new ways of efficiently combining multi-task recognition. 
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. 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. 
Applicants should have a track record of work on speech and language technologies including end to end neural systems for one or more speech labelling tasks. They should also have demonstrable hands-on experience in the implementation of complex neural systems in this domain, as well as the necessary mathematical and machine learning background. Ideally, such a track record is demonstrated by publications in international journals and conferences. Candidates are required to hold a PhD in the field and if appointed, publish results and travel to conferences.
The post holder will join the LivePerson Centre, as well as SPandH, in particular its subgroup on Machine Intelligence for Natural Interfaces. Prof. Hain, the Director of the LivePerson Centre and also Head of the SPandH group, will work closely with the successful applicant. SPandH 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
(****- a collaboration between the Natural Language Processing (NLP) research group and SPandH. Jointly, NLP and SPandH hosts more than 110 active researchers in these fields.
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