no code implementations • NAACL (BEA) 2022 • Yiting Lu, Stefano Bannò, Mark Gales
Due to a lack of end-to-end training data, SGEC is often implemented as a cascaded, modular system, consisting of speech recognition, disfluency removal, and grammatical error correction (GEC).
no code implementations • NAACL (BEA) 2022 • Stefano Bannò, Marco Matassoni
The growing demand for learning English as a second language has led to an increasing interest in automatic approaches for assessing spoken language proficiency.
no code implementations • 29 Apr 2024 • Stefano Bannò, Hari Krishna Vydana, Kate M. Knill, Mark J. F. Gales
Automated essay scoring (AES) to evaluate second language (L2) proficiency has been a firmly established technology used in educational contexts for decades.
no code implementations • 9 Nov 2023 • Stefano Bannò, Rao Ma, Mengjie Qian, Kate M. Knill, Mark J. F. Gales
This foundation model can be used to replace the whole framework or part of it, e. g., ASR and disfluency removal.
no code implementations • 16 Nov 2022 • Stefano Bannò, Kate M. Knill, Marco Matassoni, Vyas Raina, Mark J. F. Gales
Though the wav2vec 2. 0 based system is found to be sensitive to the nature of the response, it can be configured to yield comparable performance to systems requiring a speech transcription, and yields gains when appropriately combined with standard approaches.
no code implementations • 24 Oct 2022 • 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.
no code implementations • LREC 2020 • Roberto Gretter, Marco Matassoni, Stefano Bannò, Daniele Falavigna
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.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1