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The Framework of Large Audio Model based on Audio Recognition

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Xi'an Jiaotong-Liverpool University

Wuzhong District, Suzhou, China, 215000

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The Framework of Large Audio Model based on Audio Recognition

About the Project

This project aims to define and develop a Large Audio Model (LAM) framework that hierarchically models audio features to establish relationships between sound objects. Unlike traditional audio models, LAMs approach audio recognition by mimicking human perception through multi-level feature extraction and contextual understanding. The framework will integrate acoustic and semantic analysis to comprehend complex audio environments, enabling the model to perform effectively across diverse downstream tasks including classification, separation, and generation. By focusing on human recognition patterns, this research will bridge the gap between computational audio processing and perceptual understanding, creating a versatile foundation model for next-generation audio applications.

There are three more PhD projects under the supervisor of Dr. Shengchen Li are advertised at the same time. Please refer https://shengchenli.github.io/application.html for more information.

For more information about doctoral scholarship and PhD programme at Xi’an Jiaotong-Liverpool University (XJTLU), please visit:

https://www.xjtlu.edu.cn/en/admissions/global/entry-requirements/

https://www.xjtlu.edu.cn/en/admissions/global/fees-and-scholarship

Supervisors:

  • Principal supervisor: Dr. Shengchen Li (XJTLU)
  • Co-supervisor: Professor Eng Gee Lim (XJTLU)
  • Co-supervisor: Dr. Jacopo de Berardinis (UoL)
  • External supervisor: Professor Mark D. Plumbley (KCL)

Requirements:

A Master's degree with Merit and a Bachelor's degree with first-class or upper second-class honors are required for PhD admissions. Exceptional candidates holding only a Bachelor's degree may be considered on an individual basis in certain disciplines.

Evidence of good spoken and written English is essential. The candidate should have an IELTS (or equivalent) score of 6.5 or above, if the first language is not English. This position is open to all qualified candidates irrespective of nationality.

Degree:

The student will be awarded a PhD degree from the University of Liverpool (UK) upon successful completion of the program.

Funding:

The PhD studentship is available for three years subject to satisfactory progress by the student. The award covers tuition fees for three years (currently equivalent to RMB 99,000 per annum) and provides a monthly stipend of 5,000 RMB as a contribution to living expenses. It also provides up to RMB 16,500 to allow participation at international conferences during the period of the award. It is a condition of the award that holders of XJTLU PhD scholarships carry out 300-500 hours of teaching assistance work per year. The scholarship holders are expected to conduct the majority of their research at XJTLU in Suzhou, China. However, they may apply for a short-term research visit to the University of Liverpool if the project requires it.

How to Apply:

Interested applicants are advised to fill in the form at https://shengchenli.github.io/application.html with the following documents for initial review and assessment (please put the project title in the subject line).

  • CV
  • Two reference letters with company/university letterhead
  • Personal statement outlining your interest in the position
  • Proof of English language proficiency (an IELTS score of 6.5 or above)
  • Verified school transcripts in both Chinese and English (for international students, only the English version is required)
  • Verified certificates of education qualifications in both Chinese and English (for international students, only the English version is required)
  • PDF copy of Master Degree dissertation (or an equivalent writing sample) and examiners reports available

Contact:

Informal enquiries may be addressed to Dr. Shengchen Li (shengchen.li@xjtlu.edu.cn), whose personal profile is linked below:

https://scholar.xjtlu.edu.cn/en/persons/ShengchenLi/

https://shengchenli.github.io/

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