Postdoctoral Research Associate (PDRA) in Computational Linguistics
Role Description
The Department of Language and Linguistic Science is seeking to appoint a Postdoctoral Research Associate (PDRA) in Computational Linguistics for a fixed term of two years to work on “Developing Y-ACCDIST’s robustness for use on Levantine Arabic dialects”. This is a subproject of the Common European Language Indication and Analysis (CELIA) project (led by the Immigration and Naturalisation Service of the Netherlands Ministry of Asylum and Migration and co-funded by the European Union), awarded to Project Lead Dr George Brown of Lancaster University with Co-Investigator and York Lead Professor Sam Hellmuth at the University of York.
The Department is a leading centre in the UK for teaching and research in theoretical, experimental and empirical linguistics. In the most recent 2021 Research Excellence Framework, we ranked 1st overall in the UK in the Modern Languages and Linguistics unit of assessment for the quality of our research, impact and research environment. The Department Early Career Forum actively supports career development of all early career staff, including Postdoctoral Researchers, who are represented on the Department Research Committee.
Role
The role holder will form part of the small team of researchers working in Lancaster and York on the “Developing Y-ACCDIST’s robustness for use on Levantine Arabic dialects” CELIA subproject. We are looking for someone who can support development of a robust workflow for automatic speech recognition (ASR) in audio recordings of dialectal Arabic speech, to generate transcripts for use in training and testing of a system to provide semi-automatic language indications for Arabic language variants. This task entails experimentation with alternative romanised transcription systems in addition to Arabic script, and development of processes for transformation of transcripts between transcription systems, as well as development of protocols for comparative evaluation of the accuracy of different types of transcript. The subproject will be working with identified specific sources of gold-standard training data in Arabic dialects.
The ideal role holder will have experience of development and/or use of ASR workflows for dialectal Arabic speech, as well as the technical expertise to develop, document and evaluate aspects of this type of workflow. The role holder will also have a high level of proficiency in Arabic, ideally including one or more Levantine Arabic dialects, as well as an excellent command of English. Key duties and responsibilities will include:
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To support the development, documentation and evaluation of a novel workflow to provide semi-automatic language indications for Arabic language variants, in an end-use context which requires use of gold-standard training data.
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To conduct individual and collaborative research.
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To develop and initiate collaborative working internally and externally
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To undertake appropriate organisational and administrative activities connected to the project.
Skills, Experience & Qualification needed
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PhD in Linguistics or Computer Science or another related field, or equivalent experience
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Knowledge of the linguistic and computational underpinnings of speech technology
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Ability to develop solutions for an ASR workflow in appropriate coding languages e.g. Python
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High level proficiency in English and Arabic, ideally including one or more Levantine Arabic dialects
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A strong background of knowledge of speech technology and/or natural language processing applications for Arabic, and proven familiarity with the challenges of research in this area is desirable
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Experience of working with different systems for orthographic representation or transcription of dialectal Arabic is desirable
Interview date: To be confirmed
For informal enquiries: please contact Professor Sam Hellmuth on sam.hellmuth@york.ac.uk.
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