Tensor Fusion Network for Multimodal Sentiment Analysis
- Amir Zadeh, Minghai Chen, Soujanya Poria, E. Cambria, Louis-Philippe Morency
- Computer ScienceConference on Empirical Methods in Natural…
- 1 July 2017
A novel model, termed Tensor Fusion Networks, is introduced, which learns intra-modality and inter- modality dynamics end-to-end in sentiment analysis and outperforms state-of-the-art approaches for both multimodal and unimodal sentiment analysis.
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
- Amir Zadeh, Paul Pu Liang, Soujanya Poria, E. Cambria, Louis-Philippe Morency
- Computer ScienceAnnual Meeting of the Association for…
- 1 July 2018
This paper introduces CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI), the largest dataset of sentiment analysis and emotion recognition to date and uses a novel multimodal fusion technique called the Dynamic Fusion Graph (DFG), which is highly interpretable and achieves competative performance when compared to the previous state of the art.
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
- Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, E. Cambria, Rada Mihalcea
- Computer ScienceAnnual Meeting of the Association for…
- 5 October 2018
The Multimodal EmotionLines Dataset (MELD), an extension and enhancement of Emotion lines, contains about 13,000 utterances from 1,433 dialogues from the TV-series Friends and shows the importance of contextual and multimodal information for emotion recognition in conversations.
Memory Fusion Network for Multi-view Sequential Learning
- Amir Zadeh, Paul Pu Liang, N. Mazumder, Soujanya Poria, E. Cambria, Louis-Philippe Morency
- Computer ScienceAAAI Conference on Artificial Intelligence
- 1 February 2018
A new neural architecture for multi-view sequential learning called the Memory Fusion Network (MFN) is presented that explicitly accounts for both interactions in a neural architecture and continuously models them through time.
Context-Dependent Sentiment Analysis in User-Generated Videos
- Soujanya Poria, E. Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, Louis-Philippe Morency
- Computer ScienceAnnual Meeting of the Association for…
- 1 July 2017
A LSTM-based model is proposed that enables utterances to capture contextual information from their surroundings in the same video, thus aiding the classification process and showing 5-10% performance improvement over the state of the art and high robustness to generalizability.
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
- Tom Young, Devamanyu Hazarika, Soujanya Poria, E. Cambria
- Computer ScienceIEEE Computational Intelligence Magazine
- 9 August 2017
This paper reviews significant deep learning related models and methods that have been employed for numerous NLP tasks and provides a walk-through of their evolution.
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
- Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander Gelbukh, E. Cambria
- Computer ScienceAAAI Conference on Artificial Intelligence
- 1 November 2018
A new method based on recurrent neural networks that keeps track of the individual party states throughout the conversation and uses this information for emotion classification and outperforms the state of the art by a significant margin on two different datasets.
Multi-attention Recurrent Network for Human Communication Comprehension
- Amir Zadeh, Paul Pu Liang, Soujanya Poria, Prateek Vij, E. Cambria, Louis-Philippe Morency
- Computer ScienceAAAI Conference on Artificial Intelligence
- 1 February 2018
The main strength of the model comes from discovering interactions between modalities through time using a neural component called the Multi-attention Block (MAB) and storing them in the hybrid memory of a recurrent part called the Long-short Term Hybrid Memory (LSTHM).
SenticNet 3: A Common and Common-Sense Knowledge Base for Cognition-Driven Sentiment Analysis
- E. Cambria, Daniel J. Olsher, Dheeraj Rajagopal
- Computer ScienceAAAI Conference on Artificial Intelligence
- 21 June 2014
SenticNet 3 models nuanced semantics and sentics (that is, the conceptual and affective information associated with multi-word natural language expressions), representing information with a symbolic opacity of an intermediate nature between that of neural networks and typical symbolic systems.
New Avenues in Opinion Mining and Sentiment Analysis
- E. Cambria, Björn Schuller, Yunqing Xia, Catherine Havasi
- Computer ScienceIEEE Intelligent Systems
- 1 March 2013
The history, current use, and future of opinion mining and sentiment analysis are discussed, along with relevant techniques and tools.
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