Computational Modelling of Child Language Learning


   Department of Computer Science

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof Angelo Cangelosi, Dr Ben Amridge  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

The aim of this PhD project is to use cutting-edge modelling techniques to simulate children's learning of English as a native language. Although computational modelling of language has recently made significant advances e.g., ChatGPT), such models do not simulate children's language learning because (a) they are not linked to the "real-world" (grounding), (b) they receive at least 10 times more language input than children, and (c) they do not simulate children's errors (e.g., saying "Want cookie" instead of "I want a cookie" or "He go over there" instead of "He's going over there"). The aim of this project is to build a model that maps from real-world meanings and goals (e.g., [GET] [COOKIE]) to childlike utterances (e.g., "Want cookie"), and so simulates language in a 2-3 year-old child. The model will be trained using corpora of parent-child speech (e.g., https://childes.talkbank.org/access/) with utterances (e.g., "Do you want a cookie?") mapped to communicative function (e.g., QUESTION) and meaning (e.g., [LISTENER] [WANT] [COOKIE]). The result will be a model that not only simulates some of the major phenomena in child language acquisition research, but that also takes steps to address the grounding problem faced by current large language models.

This interdisciplinary project will be co-supervised by Professor Angelo Cangelosi (Computer Science), Professor Ben Ambridge (from Psychology) and Dr Colin Bannard (from Linguistics) for their interdisciplinary expertise on child language acquisition.

Eligibility

The project is suitable for a student with BSc/Master in Computer science / AI or a student with a BA/MSc in Psychology / Linguistics / Cognitive Science and good programming skills. At least a First at bachelor degree or a 2.1 at master. 

Before you apply

We strongly recommend that you contact the supervisors for this project before you apply: [Email Address Removed] and [Email Address Removed]

How to apply

Apply online through our website: https://uom.link/pgr-apply-fap 

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees. 

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. 

After you have applied you will be asked to upload the following supporting documents: 

  • Final Transcript and certificates of all awarded university level qualifications
  • Interim Transcript of any university level qualifications in progress
  • CV
  • Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
  • English Language certificate (if applicable). Most UK applicants will not need to provide English language

If you have any questions about making an application, please contact our admissions team by emailing [Email Address Removed]

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. 

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status. 

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).

Computer Science (8) Psychology (31)

Funding Notes

This PhD project is open to home students. The project is fully funded and home fees will be paid. The successful applicant will receive a tax free stipend of at least £18,622 per annum. The start date is 1st April 2024.

How good is research at The University of Manchester in Computer Science and Informatics?


Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities