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The Ministry of Language and Linguistic Sciences seeks to obtain a post-PhD research partner (PDRA) in the mathematical linguistics for a period of two years to work on “developing the Y-ACCDist durability for use on the dialects of the Levant.

The department is a pioneering center in the UK teaching and research in theoretical, experimental and experimental linguistics. In the latest framework of the 2021 research excellence, we reached the first rank in the UK in the modern language and linguistic evaluation unit to assess the quality of our research, impact and the research environment.

We are looking for a person who can support the development of a strong workflow to identify automatic speech (ASR) in the audio recordings of the Arabic dialectical discourse, to generate texts for use in training and testing a system to provide almost automatic language indicators for Arabic language variables.

The ideal role holder will have an experience in developing and/or using ASR workflow for Arabic dialectical discourse, as well as technical experience to develop, document and evaluate aspects of this type of workflow. The role holder will also have a high level of efficiency in the Arabic language, including or more dialects of the Arabic dialects, as well as an excellent leadership of the English language. It will include major duties and responsibilities:

• To support the development, documentation and evaluation of the workflow of the semi -automatic language indicators of Arabic language variables, in the context of the final use that requires training data at the gold level.
• To conduct individual and cooperative research.
• To develop and start cooperative work internally and externally
• To do the appropriate organizational and administrative activities related to the project.

The necessary skills, experience and qualifications

• Doctorate in linguistics, computer science, other related field, or an equivalent experience
• Knowing the linguistic and calculating foundations of speech technology
• The ability to develop solutions for ASR work in appropriate coding languages ​​such as Python
• High efficiency in English and Arabic, including one or more Arabic dialects
• It is advisable to have a strong background to know the technology of speech and/or applications of the natural language processing of Arabic, and its familiarity with the challenges of research in this field
• It is recommended to experience work with various systems for alphabetical or copying Arabic dialectic

Date of the interview: To be confirmed

For informal inquiries: Please call Professor Sam Helmouth Sam.helmuth@york.ac.uk.

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