no code implementations • WASSA (ACL) 2022 • Valentin Barriere, Shabnam Tafreshi, João Sedoc, Sawsan Alqahtani
This paper presents the results that were obtained from WASSA 2022 shared task on predicting empathy, emotion, and personality in reaction to news stories.
no code implementations • EACL (WASSA) 2021 • Shabnam Tafreshi, Orphee De Clercq, Valentin Barriere, Sven Buechel, João Sedoc, Alexandra Balahur
This paper presents the results that were obtained from the WASSA 2021 shared task on predicting empathy and emotions.
no code implementations • SEMEVAL 2019 • Shabnam Tafreshi, Mona Diab
Our aim is to build a robust emotion classifier that can generalize emotion detection, which is to learn emotion cues in a noisy training environment.
no code implementations • 23 May 2019 • Shabnam Tafreshi, Mona Diab
In this paper we present an emotion classifier model submitted to the SemEval-2019 Task 3: EmoContext.
no code implementations • 24 Feb 2019 • Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).
no code implementations • COLING 2018 • Shabnam Tafreshi, Mona Diab
Detection and classification of emotion categories expressed by a sentence is a challenging task due to subjectivity of emotion.