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Learning representations of emotional speech with deep convolutional generative adversarial networks
6 references·13 citing·54 second hopsampled
Learning representations of emotional speech with deep convolutional generative adversarial networks (2017)Learning representations of emotional spe…Representation Learning for Speech Emotion Recognition (2016)Representation Learning for S…Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network (2016)Adieu features? End-to-end sp…A Multi-Task Learning Framework for Emotion Recognition Using 2D Continuous Space (2015)A Multi-Task Learning Framewo…Context-Sensitive Learning for Enhanced Audiovisual Emotion Classification (2012)Context-Sensitive Learning fo…The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent (2011)The SEMAINE Database: Annotat…IEMOCAP: interactive emotional dyadic motion capture database (2008)IEMOCAP: interactive emotiona…Attention-based multimodal sentiment analysis and emotion recognition using deep neural networks (2023)Attention-based multimodal se…Deep Cross-Corpus Speech Emotion Recognition: Recent Advances and Perspectives (2021)Deep Cross-Corpus Speech Emot…DECN: Dialogical emotion correction network for conversational emotion recognition (2021)DECN: Dialogical emotion corr…Speaker-Invariant Affective Representation Learning via Adversarial Training (2020)Speaker-Invariant Affective R…Semi-supervised Multi-modal Emotion Recognition with Cross-Modal Distribution Matching (2020)Semi-supervised Multi-modal E…A Review on Five Recent and Near-Future Developments in Computational Processing of Emotion in the Human Voice (2020)A Review on Five Recent and N…A Review of Generalizable Transfer Learning in Automatic Emotion Recognition (2020)A Review of Generalizable Tra…Two-level attention with two-stage multi-task learning for facial emotion recognition (2019)Two-level attention with two-…CycleGAN-Based Emotion Style Transfer as Data Augmentation for Speech Emotion Recognition (2019)CycleGAN-Based Emotion Style …On Enhancing Speech Emotion Recognition Using Generative Adversarial Networks (2018)On Enhancing Speech Emotion R…Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes (2018)Ladder Networks for Emotion R…Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach (2018)Inferring Emotion from Conver…Pooling acoustic and lexical features for the prediction of valence (2017)Pooling acoustic and lexical …Observing Interaction: An Introduction to Sequential Analysis (1988)Praat, a system for doing phonetics by computer (2002)Annotation and processing of continuous emotional attributes: Challenges and opportunities (2013)Improving Speech Emotion Recognition with Unsupervised Representation Learning on Unlabeled Speech (2019)Multi-Task Semi-Supervised Adversarial Autoencoding for Speech Emotion Recognition (2020)Facial Action Coding System (1978)Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. 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(1954)Analysis of emotion recognition using facial expressions, speech and multimodal information (2004)A survey of speech emotion recognition in natural environment (2020)Speech emotion recognition using fusion of three multi-task learning-based classifiers: HSF-DNN, MS-CNN and LLD-RNN (2020)Survey of Deep Representation Learning for Speech Emotion Recognition (2021)A Concordance Correlation Coefficient to Evaluate Reproducibility (1989)Vocal communication of emotion: A review of research paradigms (2003)The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)Automatic speech emotion recognition using recurrent neural networks with local attention (2017)End-to-End Multimodal Emotion Recognition Using Deep Neural Networks (2017)Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers (2019)The INTERSPEECH 2009 emotion challenge (2009)A review of depression and suicide risk assessment using speech analysis (2015)Improving Speech Emotion Recognition With Adversarial Data Augmentation Network (2020)Deep learning approaches for speech emotion recognition: state of the art and research challenges (2021)SMIN: Semi-Supervised Multi-Modal Interaction Network for Conversational Emotion Recognition (2022)The expression of the emotions in man and animals. 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(1980)BReG-NeXt: Facial Affect Computing Using Adaptive Residual Networks With Bounded Gradient (2020)Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition (2021)Light Attention Embedding for Facial Expression Recognition (2021)Unsupervised learning in cross-corpus acoustic emotion recognition (2011)MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception (2016)Adversarial Auto-Encoders for Speech Based Emotion Recognition (2017)Autoencoder With Emotion Embedding for Speech Emotion Recognition (2021)Speech emotion recognition based on formant characteristics feature extraction and phoneme type convergence (2021)Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition (2022)The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression (2010)DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)Improved Speech Emotion Recognition using Transfer Learning and Spectrogram Augmentation (2021)Multimodal Emotion Recognition Using Transfer Learning from Speaker Recognition and BERT-Based Models (2022)RobinNet: A Multimodal Speech Emotion Recognition System With Speaker Recognition for Social Interactions (2022)An argument for basic emotions (1992)Emotion recognition in human-computer interaction (2001)Contextual and Cross-Modal Interaction for Multi-Modal Speech Emotion Recognition (2022)SpeechFormer: A Hierarchical Efficient Framework Incorporating the Characteristics of Speech (2022)Semantic Alignment Network for Multi-Modal Emotion Recognition (2023)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 2008IEMOCAP: interactive emotional dyadic motion capture database3,864 cited
  • 2016Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network905 cited
  • 2011The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent665 cited
  • 2015A Multi-Task Learning Framework for Emotion Recognition Using 2D Continuous Space183 cited
  • 2012Context-Sensitive Learning for Enhanced Audiovisual Emotion Classification154 cited
  • 2016Representation Learning for Speech Emotion Recognition127 cited

Cited by

  • 2019CycleGAN-Based Emotion Style Transfer as Data Augmentation for Speech Emotion Recognition87 cited
  • 2020A Review of Generalizable Transfer Learning in Automatic Emotion Recognition81 cited
  • 2020Semi-supervised Multi-modal Emotion Recognition with Cross-Modal Distribution Matching73 cited
  • 2019Two-level attention with two-stage multi-task learning for facial emotion recognition71 cited
  • 2018On Enhancing Speech Emotion Recognition Using Generative Adversarial Networks63 cited
  • 2020A Review on Five Recent and Near-Future Developments in Computational Processing of Emotion in the Human Voice61 cited
  • 2023Attention-based multimodal sentiment analysis and emotion recognition using deep neural networks60 cited

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2020
Speaker-Invariant Affective Representation Learning via Adversarial Training
57 cited
  • 2021Deep Cross-Corpus Speech Emotion Recognition: Recent Advances and Perspectives43 cited
  • 2018Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach43 cited
  • 2017Pooling acoustic and lexical features for the prediction of valence42 cited
  • 2021DECN: Dialogical emotion correction network for conversational emotion recognition42 cited
  • 2018Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes41 cited