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Multimodal Emotion Recognition

16 papers with code · Computer Vision
Subtask of Emotion Recognition

Benchmarks

Greatest papers with code

DialogueRNN: An Attentive RNN for Emotion Detection in Conversations

1 Nov 2018SenticNet/conv-emotion

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, understanding consumer feedback in live conversations, etc.

EMOTION CLASSIFICATION EMOTION RECOGNITION IN CONVERSATION MULTIMODAL EMOTION RECOGNITION

Multimodal Speech Emotion Recognition Using Audio and Text

10 Oct 2018david-yoon/multimodal-speech-emotion

Speech emotion recognition is a challenging task, and extensive reliance has been placed on models that use audio features in building well-performing classifiers.

EMOTION CLASSIFICATION MULTIMODAL EMOTION RECOGNITION MULTIMODAL SENTIMENT ANALYSIS SPEECH EMOTION RECOGNITION

End-to-End Multimodal Emotion Recognition using Deep Neural Networks

27 Apr 2017tzirakis/Multimodal-Emotion-Recognition

The system is then trained in an end-to-end fashion where - by also taking advantage of the correlations of the each of the streams - we manage to significantly outperform the traditional approaches based on auditory and visual handcrafted features for the prediction of spontaneous and natural emotions on the RECOLA database of the AVEC 2016 research challenge on emotion recognition.

MULTIMODAL EMOTION RECOGNITION

Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning

16 Apr 2018Samarth-Tripathi/IEMOCAP-Emotion-Detection

Emotion recognition has become an important field of research in Human Computer Interactions as we improve upon the techniques for modelling the various aspects of behaviour.

MOTION CAPTURE MULTIMODAL EMOTION RECOGNITION

Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in Conversation

arXiv preprint 2020 amanshenoy/multilogue-net

Sentiment Analysis and Emotion Detection in conversation is key in several real-world applications, with an increase in modalities available aiding a better understanding of the underlying emotions.

EMOTION RECOGNITION IN CONVERSATION MULTIMODAL EMOTION RECOGNITION MULTIMODAL SENTIMENT ANALYSIS