paper-with-me

Papers

A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis

2020-06-29 · WS 2020 7 · Jean-Benoit Delbrouck, Noé Tits, Mathilde Brousmiche, Stéphane Dupont

Understanding expressed sentiment and emotions are two crucial factors in human multimodal language. This paper describes a Transformer-based joint-encoding (TBJE) for the task of Emotion Recognition and Sentiment Analysis. In addition to use the Transformer architecture, our approach relies on a modular co-attention and a glimpse layer to jointly encode one or more modalities. The proposed solution has also been submitted to the ACL20: Second Grand-Challenge on Multimodal Language to be evaluated on the CMU-MOSEI dataset. The code to replicate the presented experiments is open-source: https://github.com/jbdel/MOSEI_UMONS.

📄 PDF Abstract BibTeX arXiv:2006.15955

Code (1)

jbdel/MOSEI_UMONS pytorch

Tasks

Emotion RecognitionMultimodal Sentiment AnalysisSentiment Analysis

Methods 이 논문이 사용한 방법론

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Absolute Position Encodings Absolute Position Encodings are a type of position embeddings for [Transformer-based models] where positional encodings are…
Position-Wise Feed-Forward Layer 설명 없음
Residual Connection 설명 없음
Label Smoothing Label Smoothing is a regularization technique that introduces noise for the labels. This accounts for the fact that datasets may have mistakes in them, so maximizing the…
Multi-Head Attention 설명 없음
Adam 설명 없음
ReLU How Do I Communicate to Expedia? How Do I Communicate to Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Live Support & Special Travel…

Similar Papers 제목 키워드 기반

Multimodal Emotion Recognition and Sentiment Analysis in Multi-Party Conversation Contexts

2025-03-09 · Aref Farhadipour, Hossein Ranjbar, Masoumeh Chapariniya, Teodora Vukovic 외

Emotion recognition and sentiment analysis are pivotal tasks in speech and language processing, particularly in real-world scenarios involving multi-party, conversational data. This paper presents a multimodal approach t…

Emotion RecognitionMultimodal Emotion RecognitionSentiment Analysis

Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis

2019-05-14 · NAACL 2019 6 · Md. Shad Akhtar, Dushyant Singh Chauhan, Deepanway Ghosal, Soujanya Poria 외

Related tasks often have inter-dependence on each other and perform better when solved in a joint framework. In this paper, we present a deep multi-task learning framework that jointly performs sentiment and emotion anal…

Decision MakingEmotion RecognitionMulti-Task LearningSentiment Analysis

SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images

2023-07-06 · Tuneer Khargonkar, Shwetank Choudhary, Sumit Kumar, Barath Raj KR

In this paper, we propose a sentiment-enriched lightweight network SeLiNet and an end-to-end on-device pipeline for contextual emotion recognition in images. SeLiNet model consists of body feature extractor, image aesthe…

Emotion Recognition

Leveraging Sentiment Analysis Knowledge to Solve Emotion Detection Tasks

2021-11-05 · Maude Nguyen-The, Guillaume-Alexandre Bilodeau, Jan Rockemann

Identifying and understanding underlying sentiment or emotions in text is a key component of multiple natural language processing applications. While simple polarity sentiment analysis is a well-studied subject, fewer ad…

Emotion RecognitionSentiment Analysis

MMTF-DES: A Fusion of Multimodal Transformer Models for Desire, Emotion, and Sentiment Analysis of Social Media Data

2023-10-22 · Abdul Aziz, Nihad Karim Chowdhury, Muhammad Ashad Kabir, Abu Nowshed Chy 외

Desire is a set of human aspirations and wishes that comprise verbal and cognitive aspects that drive human feelings and behaviors, distinguishing humans from other animals. Understanding human desire has the potential t…

Emotional IntelligenceEmotion RecognitionSentiment Analysis