350 citations · 652 across the 49 of their papers we have counts for
11 papers · 1 filter
L2 proficiency assessment using self-supervised speech representations
Stefano Bannò, Kate M. Knill, Marco Matassoni +2
There has been a growing demand for automated spoken language assessment systems in recent years. A standard pipeline for this process is to start with a speech recognition system…
Novel structural-scale uncertainty measures and error retention curves: application to multiple sclerosis
Nataliia Molchanova, Vatsal Raina, Andrey Malinin +6
This paper focuses on the uncertainty estimation for white matter lesions (WML) segmentation in magnetic resonance imaging (MRI). On one side, voxel-scale segmentation errors cause…
Parallel Attention Forcing for Machine Translation
Qingyun Dou, Mark Gales
Attention-based autoregressive models have achieved state-of-the-art performance in various sequence-to-sequence tasks, including Text-To-Speech (TTS) and Neural Machine Translatio…
Deliberation Networks and How to Train Them
Qingyun Dou, Mark Gales
Deliberation networks are a family of sequence-to-sequence models, which have achieved state-of-the-art performance in a wide range of tasks such as machine translation and speech…
World Knowledge in Multiple Choice Reading Comprehension
Adian Liusie, Vatsal Raina, Mark Gales
Recently it has been shown that without any access to the contextual passage, multiple choice reading comprehension (MCRC) systems are able to answer questions significantly better…
Multiple-Choice Question Generation: Towards an Automated Assessment Framework
Vatsal Raina, Mark Gales
Automated question generation is an important approach to enable personalisation of English comprehension assessment. Recently, transformer-based pretrained language models have de…
Podcast Summary Assessment: A Resource for Evaluating Summary Assessment Methods
Potsawee Manakul, Mark J. F. Gales
Automatic summary assessment is useful for both machine-generated and human-produced summaries. Automatically evaluating the summary text given the document enables, for example, s…
Gender Bias and Universal Substitution Adversarial Attacks on Grammatical Error Correction Systems for Automated Assessment
Vyas Raina, Mark Gales
Grammatical Error Correction (GEC) systems perform a sequence-to-sequence task, where an input word sequence containing grammatical errors, is corrected for these errors by the GEC…
Shifts 2.0: Extending The Dataset of Real Distributional Shifts
Andrey Malinin, Andreas Athanasopoulos, Muhamed Barakovic +15
Distributional shift, or the mismatch between training and deployment data, is a significant obstacle to the usage of machine learning in high-stakes industrial applications, such…
Residue-Based Natural Language Adversarial Attack Detection
Vyas Raina, Mark Gales
Deep learning based systems are susceptible to adversarial attacks, where a small, imperceptible change at the input alters the model prediction. However, to date the majority of t…
Self-Distribution Distillation: Efficient Uncertainty Estimation
Yassir Fathullah, Mark J. F. Gales
Deep learning is increasingly being applied in safety-critical domains. For these scenarios it is important to know the level of uncertainty in a model's prediction to ensure appro…