ALTA - Spoken Language Processing Technology Research

ALTA Spoken Language Processing Technology (SLPT) Project

[ Overview | News | Personnel ]
[ Presentations | Publications | PhD Theses]

Speak & Improve Challenge 2025

In connection with the ISCA SLaTE 2025 Workshop and Cambridge University Press and Assessment, we are happy to introduce the Speak & Improve Challenge 2025 to the speech and language learning community. Our goal is to advance the technology in the field of spoken language assessment and feedback by making available a new rich dataset and proposing a variety of associated tasks.

The challenge offers a unique opportunity with the pre-release of the Speak & Improve dataset from Cambridge University Press & Assessment. This dataset is derived from the Cambridge English Speak & Improve L2 (second language) English speaking practice tool and contains annotated recordings of a wide variety of L2 English learner speech on open (spontaneous) speaking tasks.

The challenge consists of four tasks designed to advance spoken language technology and improve automated language learning assessment and feedback: Spoken Language Assessment (SLA); Spoken Grammatical Error Correction Feedback (SGECF); Automatic Speech Recognition (ASR); and Spoken Grammatical Error Correction (SGEC). Each task has a closed and open track. Participants can do as many tasks as they would like.

Further details can be found here: Speak & Improve Challenge 2025.

Latest News

Attending COLING 2025? Our work will be featured in the main program with our paper on fine-tuning LLMs for comparative assessment and Dr Stefano Banno is a co-presenter of the tutorial on LLMs in Education: Novel Perspectives, Challenges, and Opportunities
Adian Liusie defended his PhD on mitigating and analysing bias in LLMs
Paper presented at SLT 2024 on controlling Whisper
Four papers presented at EMNLP 2024 (is LLM-as-a-Judge robust?, efficient comparative assessment, muting Whisper and effect of task-switching on LLMs) and one at FEVER (question-based retrieval for Enterprise RAG)
Two papers (add a language to Whisper and articulatory modelling) presented at InterSpeech 2024
Potsawee Manakul has successfully defended his PhD thesis on abstractive summarization and information consistency assessment
Dr Mengjie Qian gave an invited talk at the Second Language Acquisition with Speech and Language Technologies (SLASaLT) Workshop, in Sheffield on 18th June on the Automatic Language Teaching and Assessment (ALTA) Spoken Language Processing Technology Project: ALTA Speaking.
Two papers (NLP task analysis and debiasing) presented at ACL 2024 (1 main, 1 findings)
Paper on GPT4 for analytic assessment presented at BEA 2024 Workshop
Three papers presented at NAACL 2024 (2 main conference, 1 findings)

Openings

We do not have any open positions currently.

Overview

The Cambridge Institute for Automated Language Teaching and Assessment (ALTA) is a virtual institute that brings together researchers from Cambridge University Press & Assessment and the departments of Computer Science and Technology and Engineering. Using techniques from Machine Learning and Natural Language Processing, ALTA's primary objective is to develop technology to enhance the experience of language learning and to develop cutting-edge approaches to automated assessment that 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:

language assessment;
teaching feedback;
adaptive learning;
content creation and calibration.

The institute comprises researchers at the Department of Computer Science and Technology (CST) and the Department of Engineering (CUED), organised into a consortium of projects. The CUED project is:

Spoken Language Processing Technology (SLPT)

The ALTA 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.

Try it out: practise speaking English with Speak&Improve

Please email Kate Knill kmk1001 @ cam.ac.uk if you have any questions.

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