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20202026
most citedTLT-school: a Corpus of Non Native Children Speech

13 citations · 20 across the 17 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CL2025

Data Augmentation for Spoken Grammatical Error Correction

Penny Karanasou, Mengjie Qian, Stefano Bannò +2

While there exist strong benchmark datasets for grammatical error correction (GEC), high-quality annotated spoken datasets for Spoken GEC (SGEC) are still under-resourced. In this…

eess.AS2025

Natural Language-based Assessment of L2 Oral Proficiency using LLMs

Stefano Bannò, Rao Ma, Mengjie Qian +3

Natural language-based assessment (NLA) is an approach to second language assessment that uses instructions - expressed in the form of can-do descriptors - originally intended for…

cs.CL2025

Opportunities and Challenges of LLMs in Education: An NLP Perspective

Sowmya Vajjala, Bashar Alhafni, Stefano Bannò +2

Interest in the role of large language models (LLMs) in education is increasing, considering the new opportunities they offer for teaching, learning, and assessment. In this paper,…

cs.CL2025

End-to-End Spoken Grammatical Error Correction

Mengjie Qian, Rao Ma, Stefano Bannò +2

Grammatical Error Correction (GEC) and feedback play a vital role in supporting second language (L2) learners, educators, and examiners. While written GEC is well-established, spok…

cs.CL2025

Exploiting the English Vocabulary Profile for L2 word-level vocabulary assessment with LLMs

Stefano Bannò, Kate Knill, Mark Gales

Vocabulary use is a fundamental aspect of second language (L2) proficiency. To date, its assessment by automated systems has typically examined the context-independent, or part-of-…

cs.CL2025

Assessment of L2 Oral Proficiency using Speech Large Language Models

Rao Ma, Mengjie Qian, Siyuan Tang +3

The growing population of L2 English speakers has increased the demand for developing automatic graders for spoken language assessment (SLA). Historically, statistical models, text…

cs.CL2025

Scaling and Prompting for Improved End-to-End Spoken Grammatical Error Correction

Mengjie Qian, Rao Ma, Stefano Bannò +2

Spoken Grammatical Error Correction (SGEC) and Feedback (SGECF) are crucial for second language learners, teachers and test takers. Traditional SGEC systems rely on a cascaded pipe…