🧑‍🔬 Stefano Bannò

🏛️ Affiliations

🎓University of CambridgeCambridge · United Kingdom2023–2026 · 16 papersEmployment since 2023 · Research Associate, Department of Engineeringcurrent🎓University of TrentoTrento · Italy2022–2023 · 6 papers🔬Fondazione Bruno KesslerTrento · Italy2022–2023 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Proficiency assessment of L2 spoken English using wav2vec 2.0 (2022 · 35 citations)
   The paper tackles automatic grading of spoken English produced by second-language learners. Most earlier graders rely either on hand-engineered features, which may miss useful cues, or on ASR transcripts, which carry recognition errors and lose prosodic information. The authors instead fine-tune the self-supervised…
2. Cross-corpora experiments of automatic proficiency assessment and error detection for spoken English (2022 · 9 citations)
   The paper addresses automatic scoring of spoken answers from learners of English as a second language. Two obstacles motivate it: annotated speech data is scarce, and human raters are often inconsistent. The authors treat grammatical errors as a stable signal of proficiency and transfer knowledge from writing to…
3. Exploiting the English Vocabulary Profile for L2 word-level vocabulary assessment with LLMs (2025 · 8 citations)
   The paper addresses fine-grained L2 vocabulary assessment. Instead of scoring whole essays or tagging words by part of speech alone, it gives each word a CEFR level based on the sense it carries in its sentence. The authors pair LLMs with the English Vocabulary Profile (EVP), a public resource built from the…
4. Speak & Improve Challenge 2025: Tasks and Baseline Systems (2024 · 3 citations)
   Building automatic tools that grade learner speech and give feedback is difficult. Learners speak spontaneously, the content is not known in advance, and their accents and grammar differ from L1 speakers. Progress has also been held back by a lack of well-labelled public data. The authors launch the Speak & Improve…
5. Exploiting the English Grammar Profile for L2 grammatical analysis with LLMs (2026 · 1 citation)
   The paper tackles automatic analysis of L2 English grammar that goes beyond error spotting. It also records which constructions learners attempt and whether they get them right. The authors build on the English Grammar Profile (EGP), a catalogue of over 1,000 constructs. Each construct is written as a can-do…
6. Opportunities and Challenges of LLMs in Education: An NLP Perspective (2026)
   This position-and-survey paper looks at how large language models are changing educational NLP. Earlier overviews were mostly aimed at education-technology readers or covered only narrow areas such as writing assessment. The authors instead write for NLP researchers and tie recent LLM work back to older lines of NLP…

🤝 Co-authors here

10 co-authors with a page, the most papers together first.

• Kate Knill ×3
• Mark Gales ×3
• Marco Matassoni ×2
• Penny Karanasou ×2
• Bashar Alhafni
• Diane Nicholls
• Ekaterina Kochmar
• Kaushal Kumar Maurya
• Mengjie Qian
• Sowmya Vajjala

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Workshop on Innovative Use of NLP for Building Educational Applications (BEA) ×3: BEA 2026, BEA 2025, BEA 2022
• IEEE Spoken Language Technology Workshop (SLT): SLT 2022

🔗 Cited by

Papers of our library cite their works 27 times (of the 149,439 papers whose bibliographies we read); 10 citing papers with a page here →.

Updated 1 November 2026

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