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Deep Multimodal K-Fold Model for Emotion and Sentiment Analysis in Figurative Language
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inferredcites →https://doi.org/10.1007/978-981-33-4073-2_4openalex-extracted
Deep Classification of Sound: A Concise Review
inferredcites →https://doi.org/10.1007/s11042-017-5539-3openalex-extracted
Spectrogram based multi-task audio classification
inferredcites →https://doi.org/10.1007/s11042-022-12411-3openalex-extracted
Emotion detection from multilingual audio using deep analysis
inferredcites →https://doi.org/10.1007/s11042-022-13448-0openalex-extracted
Early-production stage prediction of movies success using K-fold hybrid deep ensemble learning model
inferredcites →https://doi.org/10.1007/s13278-018-0505-2openalex-extracted
Emotion detection from text and speech: a survey
inferredcites →https://doi.org/10.1016/j.eswa.2020.114177openalex-extracted
MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach
inferredcites →https://doi.org/10.1016/j.eswa.2021.114683openalex-extracted
Speech emotion recognition using recurrent neural networks with directional self-attention
inferredcites →https://doi.org/10.1016/j.inffus.2017.02.003openalex-extracted
A review of affective computing: From unimodal analysis to multimodal fusion
inferredcites →https://doi.org/10.1016/j.iot.2022.100636openalex-extracted
A machine-learning ensemble model for predicting energy consumption in smart homes
inferredcites →https://doi.org/10.1016/j.jocs.2017.01.010openalex-extracted
Extraction of emotions from multilingual text using intelligent text processing and computational linguistics
inferredcites →https://doi.org/10.1016/j.specom.2010.08.013openalex-extracted
Automatic speech emotion recognition using modulation spectral features
inferredcites →https://doi.org/10.1093/oso/9780195112719.001.0001openalex-extracted
The Expression Of The Emotions In Man And Animals
inferredcites →https://doi.org/10.1109/access.2020.3035910openalex-extracted
Ensemble Learning With Attention-Integrated Convolutional Recurrent Neural Network for Imbalanced Speech Emotion Recognition
inferredcites →https://doi.org/10.1109/dest.2010.5610650openalex-extracted
Computational approaches for emotion detection in text
inferredcites →https://doi.org/10.1109/icassp.2017.7952552openalex-extracted
Automatic speech emotion recognition using recurrent neural networks with local attention
inferredcites →https://doi.org/10.1109/iccsea54677.2022.9936080openalex-extracted
Deep Analysis for Speech Emotion Recognization
inferredcites →https://doi.org/10.1109/icime.2009.113openalex-extracted
Towards Text-based Emotion Detection A Survey and Possible Improvements
inferredcites →https://doi.org/10.1109/mis.2016.94openalex-extracted
Multimodal Sentiment Intensity Analysis in Videos: Facial Gestures and Verbal Messages
inferredcites →https://doi.org/10.1109/taffc.2014.2317187openalex-extracted
Are They Different? Affect, Feeling, Emotion, Sentiment, and Opinion Detection in Text
inferredcites →https://doi.org/10.1109/tpami.2018.2798607openalex-extracted
Multimodal Machine Learning: A Survey and Taxonomy
inferredcites →https://doi.org/10.1145/3136755.3136801openalex-extracted
Multimodal sentiment analysis with word-level fusion and reinforcement learning
inferredcites →https://doi.org/10.1186/s13636-021-00208-5openalex-extracted
End-to-end speech emotion recognition using a novel context-stacking dilated convolution neural network
inferredcites →https://doi.org/10.1609/aaai.v32i1.12024openalex-extracted
Multi-attention Recurrent Network for Human Communication Comprehension
inferredcites →https://doi.org/10.1609/aaai.v33i01.33016892openalex-extracted
Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities
inferredcites →https://doi.org/10.1609/aaai.v33i01.33017216openalex-extracted
Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors
inferredcites →https://doi.org/10.1613/jair.953openalex-extracted
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.18653/v1/d17-1openalex-extracted
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
inferredcites →https://doi.org/10.18653/v1/d17-1115openalex-extracted
Tensor Fusion Network for Multimodal Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/d18-1382openalex-extracted
Contextual Inter-modal Attention for Multi-modal Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/n19-1034openalex-extracted
Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/p17-1081openalex-extracted
Context-Dependent Sentiment Analysis in User-Generated Videos
inferredcites →https://doi.org/10.18653/v1/p18-1208openalex-extracted
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
inferredcites →https://doi.org/10.18653/v1/p18-1209openalex-extracted
Efficient Low-rank Multimodal Fusion With Modality-Specific Factors
inferredcites →https://doi.org/10.18653/v1/p19-1046openalex-extracted
Divide, Conquer and Combine: Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing
inferredcites →https://doi.org/10.18653/v1/w18-3301openalex-extracted
Getting the subtext without the text: Scalable multimodal sentiment classification from visual and acoustic modalities
inferredcites →https://doi.org/10.25080/majora-7b98e3ed-003openalex-extracted
librosa: Audio and Music Signal Analysis in Python
inferredcites →https://doi.org/10.3115/v1/w14-6905openalex-extracted
Emotion Detection from text: A Survey
inferredcites →https://doi.org/10.48550/arxiv.1806.00064openalex-extracted
Efficient Low-rank Multimodal Fusion with Modality-Specific Factors
inferredcites →https://doi.org/10.48550/arxiv.1806.06176openalex-extracted
Learning Factorized Multimodal Representations
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