131 citations · 291 across the 34 of their papers we have counts for
6 papers · 1 filter
Attentive Modality Hopping Mechanism for Speech Emotion Recognition
Seunghyun Yoon, Subhadeep Dey, Hwanhee Lee +1
In this work, we explore the impact of visual modality in addition to speech and text for improving the accuracy of the emotion detection system. The traditional approaches tackle…
Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks
Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim +2
In this study, we propose a novel graph neural network called propagate-selector (PS), which propagates information over sentences to understand information that cannot be inferred…
Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model
Jiin Nam, Seunghyun Yoon, Kyomin Jung
While deep learning techniques have shown promising results in many natural language processing (NLP) tasks, it has not been widely applied to the clinical domain. The lack of larg…
Effective Sentence Scoring Method using Bidirectional Language Model for Speech Recognition
Joongbo Shin, Yoonhyung Lee, Kyomin Jung
In automatic speech recognition, many studies have shown performance improvements using language models (LMs). Recent studies have tried to use bidirectional LMs (biLMs) instead of…
Speech Emotion Recognition Using Multi-hop Attention Mechanism
Seunghyun Yoon, Seokhyun Byun, Subhadeep Dey +1
In this paper, we are interested in exploiting textual and acoustic data of an utterance for the speech emotion classification task. The baseline approach models the information fr…
A Compare-Aggregate Model with Latent Clustering for Answer Selection
Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim +2
In this paper, we propose a novel method for a sentence-level answer-selection task that is a fundamental problem in natural language processing. First, we explore the effect of ad…