no code implementations • EMNLP 2020 • Sungho Jeon, Michael Strube
We approximate a linguistic theory of coherence, Centering theory, which we use to track the changes of focus between discourse segments.
1 code implementation • EMNLP (sustainlp) 2021 • Sungho Jeon, Michael Strube
In this work, we first show that state-of-the-art systems, recent neural essay scoring systems, might be also influenced by the correlation between essay length and scores in a standard dataset.
Ranked #2 on Automated Essay Scoring on ASAP
1 code implementation • ACL 2022 • Sungho Jeon, Michael Strube
We evaluate our model on three downstream tasks showing that it is not only linguistically more sound than previous models but also that it outperforms them in end applications.
no code implementations • 5 Nov 2023 • Sungho Jeon, Ching-Feng Yeh, Hakan Inan, Wei-Ning Hsu, Rashi Rungta, Yashar Mehdad, Daniel Bikel
In this paper, we show that a simple self-supervised pre-trained audio model can achieve comparable inference efficiency to more complicated pre-trained models with speech transformer encoders.
1 code implementation • COLING 2020 • Sungho Jeon, Michael Strube
We propose a coherence model which interprets sentences incrementally to capture lexical relations between them.
1 code implementation • 20 Jan 2017 • Sungho Jeon, Jong-Woo Shin, Young-Jun Lee, Woong-Hee Kim, YoungHyoun Kwon, Hae-Yong Yang
This work aims to investigate the use of deep neural network to detect commercial hobby drones in real-life environments by analyzing their sound data.