[Univ of Cambridge] [Dept of Engineering]

ALTA - Spoken Language Research @CUED

[ Description | Personnel | Publications ]



The Cambridge University Institute for Automated Language Teaching and Assessment (ALTA) is a virtual institute which brings together teams from computing, engineering, linguistics and language assessment to investigate new ways of using technology to enhance language learning and to develop cutting-edge approaches to assessment which will benefit learners and teachers worldwide. It forms part of Cambridge University's Language Sciences Interdisciplinary Research Center.

Sponsorship from Cambridge Assessment English supports a team of PhD students and post-doctoral researchers who investigate a range of topics, including:

  • text and speech processing;
  • machine learning;
  • corpus development and analysis;
  • security, platforms and deployment.

The institute comprises researchers at the Department of Computer Science and Technology (CST) and the Department of Engineering (CUED). The principal investigators, and research areas, are:

The research in the CUED Speech Group is focused on spoken language assessment and learning. The group works on all aspects of this area from core speech recognition and machine learning, to spoken language assessment, to feedback and the nature of the test.

Personnel Associated with ALTA @CUED

Former members:

  • Karl Bates [UGrad student]
  • Dr Jeff Chen [Research Associate]
  • Dr Rogier van Dalen [Research Associate]
  • Shixiang Gu [Research Student (part funded)]
  • Prof D. Littman [Visitor]
  • Hanxu Lu [UROP/UGrad student]
  • Zhi Chen Neo [UROP student]
  • Junjie Pan [MPhil student]
  • Sebastian Popescu [MPhil student]
  • Dr Anton Ragni [Research Associate]
  • Mohammad Rashid [MPhil student]
  • Marco del Vecchio [MPhil student]
  • Yisheng Xu [UGrad student]


[ Assessment Systems | Speech Recognition ]
[Off-Topic Detection | Feedback | Machine Learning ]

Assessment Systems and Infrastructure

Automatic Speech Recognition

Off-Topic Response Detection

Feedback (Pronunciation and Grammar)

Machine Learning

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