Investigating the potential of NLP-driven linguistic and acoustic features for predicting human scores of children’s oral language proficiency-Reference-Cited by-同舟云学术

Investigating the potential of NLP-driven linguistic and acoustic features for predicting human scores of children’s oral language proficiency

Published:2021-07-04 Issue:4 Volume:28 Page:477-505
ISSN:0969-594X
Container-title:Assessment in Education: Principles, Policy & Practice
language:en
Short-container-title:Assessment in Education: Principles, Policy & Practice

Author:

Hunte Melissa R.¹^ORCID,McCormick Samantha¹^ORCID,Shah Maitree²^ORCID,Lau Clarissa¹^ORCID,Jang Eunice Eunhee¹

Affiliation:

1. Applied Psychology and Human Development, University of Toronto, Toronto, ON, Canada

2. Electrical & Computer Engineering, University of Toronto, Toronto, On, Canada

Publisher

Informa UK Limited

Subject

Education

Link

https://www.tandfonline.com/doi/pdf/10.1080/0969594X.2021.1999209

Reference114 articles.

1. Albrecht, S., Cullen, C., Davies, K., Dunlop, M., Elliott, M. & Stevenson, L. (2018). Cambridge Assessment English. Cambridge University Press. https://www.cambridgeenglish.org/Images/461823-young-learners-revision-publication.pdf

2. Amazon Web Services (AWS). (2016). Amazon Polly [Text-to-Speech Service]. www.aws.amazon.com/polly/

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