Do face masks introduce bias in speech technologies? The case of automated scoring of speaking proficiency

no code implementations • 17 Aug 2020 • Anastassia Loukina, Keelan Evanini, Matthew Mulholland, Ian Blood, Klaus Zechner

However, these differences do not lead to differences in human or automated scores of English language proficiency.

Exploring Recurrent, Memory and Attention Based Architectures for Scoring Interactional Aspects of Human-Machine Text Dialog

no code implementations • 20 May 2020 • Vikram Ramanarayanan, Matthew Mulholland, Debanjan Ghosh

An important step towards enabling English language learners to improve their conversational speaking proficiency involves automated scoring of multiple aspects of interactional competence and subsequent targeted feedback.

Word-Embedding based Content Features for Automated Oral Proficiency Scoring

no code implementations • WS 2018 • Su-Youn Yoon, Anastassia Loukina, Chong MIn Lee, Matthew Mulholland, Xinhao Wang, Ikkyu Choi

speech-recognition Speech Recognition +1

Enhancing STEM Motivation through Personal and Communal Values: NLP for Assessment of Utility Value in Student Writing

no code implementations • WS 2016 • Beata Beigman Klebanov, Jill Burstein, Judith Harackiewicz, Stacy Priniski, Matthew Mulholland

Predicting Grammaticality on an Ordinal Scale

no code implementations • ACL 2014 • Michael Heilman, Aoife Cahill, Nitin Madnani, Melissa Lopez, Matthew Mulholland, Joel Tetreault

Automated Essay Scoring Language Modelling +5

Suicidal Tendencies: The Automatic Classification of Suicidal and Non-Suicidal Lyricists Using NLP

no code implementations • IJCNLP 2013 • Matthew Mulholland, Joanne Quinn

General Classification