collaborators

19 papers

cs.AI2026

Bias Analysis of L2 Speaking Assessment Systems Using Concept Activation Vectors

Arya Labroo, Mengjie Qian, Kate Knill

Automatic speaking assessment systems are increasingly deployed in high-stakes settings to mark second language (L2) learners' speaking tests, making it critical to show that their…

cs.CL2026

Controlling Implicit Shortcut Reliance in L2 Spoken English Auto-markers

Shilin Gao, Mark J. F. Gales, Kate M. Knill

Increasingly, speech and language processing tasks take either audio or text directly rather than extracting features from these as the input to the classifier or regressor. Often…

eess.AS2026

Data Augmentation for L2 English Speaking Assessment using TTS

Stefano Bannò, Penny Karanasou, Mengjie Qian +2

Automated assessment of second language (L2) speaking proficiency relies on large-scale annotated speech data, which remains scarce compared to widely available written learner cor…

eess.AS2026

Detect, Attend and Extract: Keyword Guided Target Speaker Extraction

Haoyu Li, Yu Xi, Yidi Jiang +5

Target speaker extraction (TSE) aims to extract the speech of a target speaker from mixtures containing multiple competing speakers. Conventional TSE systems predominantly rely on…

cs.CL2026

To Be Multimodal or Not to Be: Query-Adaptive Audio-Visual Person Retrieval via Active Modality Detection

Erfan Loweimi, Mengjie Qian, Kate Knill +7

When retrieving a person from a video archive by voice and face, should the system be multimodal or not? In real-world broadcast archives, unlike curated benchmarks, a target may b…

cs.CL2026

Who can we trust? LLM-as-a-jury for Comparative Assessment

Mengjie Qian, Guangzhi Sun, Mark J. F. Gales +1

Large language models (LLMs) are increasingly applied as automatic evaluators for natural language generation assessment often using pairwise comparative judgements. Existing appro…