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SUMMARY:Cross-corpora experiments of automatic proficiency assessment and 
 error detection for spoken English - Stefano Bannò (University of Trento)
DTSTART:20211108T120000Z
DTEND:20211108T130000Z
UID:TALK165694@talks.cam.ac.uk
CONTACT:Dr Jie Pu
DESCRIPTION:*Abstract*: Automatic scoring of language proficiency is becom
 ing a point of growing importance because the number of English-as-a-secon
 d-language learners has been steadily increasing worldwide. Two common iss
 ues in this field are: a) the lack of publicly available data specifically
  designed and annotated for automatic assessment\, especially as regards s
 poken data\, and b) the lack of consistency and coherence in human assessm
 ent. Although second language proficiency cannot be assessed on the mere b
 asis of the presence of errors\, this aspect is highly consistent. In this
  talk\, we will present an approach to automatically predict the scores of
  spoken language responses of ESL learners (TLT-school corpus and ICNALE c
 orpus) leveraging written data (EFCAMDAT corpus) and exploiting the presen
 ce of grammatical errors modelled across 5 CEFR proficiency levels thus ta
 ckling both the aforementioned problems.\n\n*Bio*: Stefano Bannò is a sec
 ond-year PhD student in Cognitive Science at University of Trento in a joi
 nt programme with the SpeechTeK research unit of Fondazione Bruno Kessler 
 (FBK) with a project on automatic assessment of spoken language proficienc
 y. Before starting the doctoral course\, he obtained a MA in Philology and
  Linguistics and a BA in Classics at University of Trento. During his MA\,
  he spent a research period at the Lautarchiv of Humboldt University in Be
 rlin. Besides his academic career\, he has worked as a musician and a seco
 ndary school teacher. He is currently working at the Department of Enginee
 ring at Cambridge University as a visiting student.
LOCATION:Zoom: https://eng-cam.zoom.us/j/81927138251?pwd=TVd3MXliV003dUdYV
 lFwU2NDWGpmdz09
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