228 citations · 562 across the 34 of their papers we have counts for
13 papers · 1 filter
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
Navonil Majumder, Soujanya Poria, Devamanyu Hazarika +3
Emotion detection in conversations is a necessary step for a number of applications, including opinion mining over chat history, social media threads, debates, argumentation mining…
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
Soujanya Poria, Devamanyu Hazarika, Navonil Majumder +3
Emotion recognition in conversations is a challenging task that has recently gained popularity due to its potential applications. Until now, however, a large-scale multimodal multi…
Semantically Enhanced Models for Commonsense Knowledge Acquisition
Ikhlas Alhussien, Erik Cambria, Zhang NengSheng
Commonsense knowledge is paramount to enable intelligent systems. Typically, it is characterized as being implicit and ambiguous, hindering thereby the automation of its acquisitio…
Concept-Based Embeddings for Natural Language Processing
Yukun Ma, Erik Cambria
In this work, we focus on effectively leveraging and integrating information from concept-level as well as word-level via projecting concepts and words into a lower dimensional spa…
GPU-based Commonsense Paradigms Reasoning for Real-Time Query Answering and Multimodal Analysis
Nguyen Ha Tran, Erik Cambria
We utilize commonsense knowledge bases to address the problem of real- time multimodal analysis. In particular, we focus on the problem of multimodal sentiment analysis, which cons…
Multimodal Sentiment Analysis using Hierarchical Fusion with Context Modeling
N. Majumder, D. Hazarika, A. Gelbukh +2
Multimodal sentiment analysis is a very actively growing field of research. A promising area of opportunity in this field is to improve the multimodal fusion mechanism. We present…