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

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

collaborators

18 papers

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 requires substantial annotated speech data, which are scarce compared to written learner corpora. We investigate w…

cs.CL2026

Towards Self-Referential Analytic Assessment: A Profile-Based Approach to L2 Writing Evaluation with LLMs

Stefano Bannò, Kate Knill, Mark Gales

Automated essay scoring (AES) research often relies on rank-based correlation metrics to validate analytic assessment. However, such metrics obscure both intrinsic intercorrelation…

cs.CL2026

Exploiting the English Grammar Profile for L2 grammatical analysis with LLMs

Stefano Bannò, Penny Karanasou, Kate Knill +1

Evaluating the grammatical competence of second language (L2) learners is essential both for providing targeted feedback and for assessing proficiency. To achieve this, we propose…

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…

cs.CL2024

Speak & Improve Challenge 2025: Tasks and Baseline Systems

Mengjie Qian, Kate Knill, Stefano Banno +4

This paper presents the "Speak & Improve Challenge 2025: Spoken Language Assessment and Feedback" -- a challenge associated with the ISCA SLaTE 2025 Workshop. The goal of the chall…

cs.CL2024★ 1 cited

LLMs in Education: Novel Perspectives, Challenges, and Opportunities

Bashar Alhafni, Sowmya Vajjala, Stefano Bannò +2

The role of large language models (LLMs) in education is an increasing area of interest today, considering the new opportunities they offer for teaching, learning, and assessment.…

cs.CL2024

Grammatical Error Feedback: An Implicit Evaluation Approach

Stefano Bannò, Kate Knill, Mark J. F. Gales

Grammatical feedback is crucial for consolidating second language (L2) learning. Most research in computer-assisted language learning has focused on feedback through grammatical er…

cs.CL2024

Can GPT-4 do L2 analytic assessment?

Stefano Bannò, Hari Krishna Vydana, Kate M. Knill +1

Automated essay scoring (AES) to evaluate second language (L2) proficiency has been a firmly established technology used in educational contexts for decades. Although holistic scor…

cs.CL2023

Towards End-to-End Spoken Grammatical Error Correction

Stefano Bannò, Rao Ma, Mengjie Qian +2

Grammatical feedback is crucial for L2 learners, teachers, and testers. Spoken grammatical error correction (GEC) aims to supply feedback to L2 learners on their use of grammar whe…

eess.AS2022★ 3 cited

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…

cs.CL2022★ 3 cited

Proficiency assessment of L2 spoken English using wav2vec 2.0

Stefano Bannò, Marco Matassoni

The increasing demand for learning English as a second language has led to a growing interest in methods for automatically assessing spoken language proficiency. Most approaches us…

cs.CL2020★ 13 cited

TLT-school: a Corpus of Non Native Children Speech

Roberto Gretter, Marco Matassoni, Stefano Bannò +1

This paper describes "TLT-school" a corpus of speech utterances collected in schools of northern Italy for assessing the performance of students learning both English and German. T…