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An Interaction-aware Attention Network for Speech Emotion Recognition in Spoken Dialogs

https://doi.org/10.1109/icassp.2019.8683293
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-031-02134-3openalex-snapshot
Spoken Dialogue Systems
inferredcites →https://doi.org/10.1007/s10579-008-9076-6openalex-snapshot
IEMOCAP: interactive emotional dyadic motion capture database
inferredcites →https://doi.org/10.1073/pnas.1616056114openalex-snapshot
Mental models accurately predict emotion transitions
inferredcites →https://doi.org/10.1080/02699931.2015.1056107openalex-snapshot
The role of emotion transition for the perception of social dominance and affiliation
inferredcites →https://doi.org/10.1109/icassp.2003.1202279openalex-snapshot
Hidden Markov model-based speech emotion recognition
inferredcites →https://doi.org/10.1109/icassp.2010.5494890openalex-snapshot
Decision level combination of multiple modalities for recognition and analysis of emotional expression
inferredcites →https://doi.org/10.1109/icassp.2016.7472669openalex-snapshot
Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network
inferredcites →https://doi.org/10.1109/icassp.2017.7952552openalex-snapshot
Automatic speech emotion recognition using recurrent neural networks with local attention
inferredcites →https://doi.org/10.1109/icme.2003.1220939openalex-snapshot
Hidden Markov model-based speech emotion recognition
inferredcites →https://doi.org/10.1109/icmlc.2005.1527805openalex-snapshot
Speech emotion recognition based on HMM and SVM
inferredcites →https://doi.org/10.1109/jproc.2012.2236291openalex-snapshot
Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language
inferredcites →https://doi.org/10.1109/msp.2017.2718581openalex-snapshot
Signal Processing and Machine Learning for Mental Health Research and Clinical Applications [Perspectives]
inferredcites →https://doi.org/10.1109/tsa.2004.838534openalex-snapshot
Toward detecting emotions in spoken dialogs
inferredcites →https://doi.org/10.1145/1873951.1874246openalex-snapshot
Opensmile
inferredcites →https://doi.org/10.1609/aaai.v32i1.11280openalex-snapshot
Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach
inferredcites →https://doi.org/10.18653/v1/n18-1193openalex-snapshot
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
inferredcites →https://doi.org/10.21437/interspeech.2014-57openalex-snapshot
Speech emotion recognition using deep neural network and extreme learning machine
inferredcites →https://doi.org/10.21437/interspeech.2017-713openalex-snapshot
Interaction and Transition Model for Speech Emotion Recognition in Dialogue
inferredcites →https://doi.org/10.2200/s00204ed1v01y200910hlt005openalex-snapshot
Spoken Dialogue Systems
inferredcites →https://doi.org/10.2307/3094912openalex-snapshot
The Ripple Effect: Emotional Contagion and its Influence on Group Behavior
inferredcites →https://doi.org/10.3109/14015439709075330openalex-snapshot
On the perception of emotions in speech: the role of voice quality
inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-snapshot
Neural Machine Translation by Jointly Learning to Align and Translate
inferredcites →https://doi.org/10.48550/arxiv.1412.3555openalex-snapshot
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Segmentwise Multilayer Perceptrons for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.1007/978-981-96-1045-7_29openalex-snapshot
DA-KWFormer: A Domain Adaptation Network with K-Weight Transformer for Speech Emotion Recognition
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TWACapsNet: a capsule network with two-way attention mechanism for speech emotion recognition
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Speech emotion recognition in conversations using artificial intelligence: a systematic review and meta-analysis
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CCTG-NET: Contextualized Convolutional Transformer-GRU Network for speech emotion recognition
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Affect-GCN: a multimodal graph convolutional network for multi-emotion with intensity recognition and sentiment analysis in dialogues
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A novel conversational hierarchical attention network for speech emotion recognition in dyadic conversation
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Teaming with Artificial Intelligence to Learn and Sustain Psychotherapy Delivery Skills: Workplace, Ethical, and Research Implications
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MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach
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Semi-supervised emotion recognition in textual conversation via a context-augmented auxiliary training task
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Learning affective representations based on magnitude and dynamic relative phase information for speech emotion recognition
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Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
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Residual Relation-Aware Attention Deep Graph-Recurrent Model for Emotion Recognition in Conversation
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Auto-correlation for Predicting Neutral Emotion State on Speech Emotion Recognition
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Research on Emotion Prediction Based on Emotional Changes in Dialogue Scenarios
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Multimodal Emotion Recognition from Voice and Video Signals
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MAEC: Multi-Instance Learning with an Adversarial Auto-Encoder-Based Classifier for Speech Emotion Recognition
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A Novel end-to-end Speech Emotion Recognition Network with Stacked Transformer Layers
inferred← citeshttps://doi.org/10.1109/icassp39728.2021.9414489openalex-snapshot
A Novel Attention-Based Gated Recurrent Unit and its Efficacy in Speech Emotion Recognition
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Hierarchical Network Based on the Fusion of Static and Dynamic Features for Speech Emotion Recognition
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A Dialogical Emotion Decoder for Speech Emotion Recognition in Spoken Dialog
inferred← citeshttps://doi.org/10.1109/icassp40776.2020.9054629openalex-snapshot
Speech Emotion Recognition with Dual-Sequence LSTM Architecture
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A Commonsense Knowledge Enhanced Network with Retrospective Loss for Emotion Recognition in Spoken Dialog
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Modeling Intrapersonal and Interpersonal Influences for Automatic Estimation of Therapist Empathy in Counseling Conversation
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FIDIC:Fine-Grained Conversational Emotion Recognition via Individual Differences in Inertia and Contagion
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A Lightweight Speech Emotion Recognition Model with Bias-Focal Loss
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Emotional Acceptance Measure (EAM): An Objective Evaluation Method Towards Information Communication Effect
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A Hierarchical Speech Emotion Classification Framework based on Joint Triplet-Center Loss
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Enhanced Emotion Recognition Through Multimodal Fusion Using TriModal Fusion Graph Convolutional Networks
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Distribution-Based Emotion Recognition in Conversation
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Survey of Deep Representation Learning for Speech Emotion Recognition
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Speech Emotion Recognition on Small Sample Learning by Hybrid WGAN-LSTM Networks
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Art appreciation model design based on improved PageRank and ECA-ResNeXt50 algorithm
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