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Hybrid CNN-BiLSTM architecture with multiple attention mechanisms to enhance speech emotion recognition
16 references·0 citing·32 second hop
Hybrid CNN-BiLSTM architecture with multiple attention mechanisms to enhance speech emotion recognition (2024)Hybrid CNN-BiLSTM architecture with multi…Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects (2023)Deep learning-based multimoda…CTNet: Conversational Transformer Network for Emotion Recognition (2021)CTNet: Conversational Transfo…Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers (2019)Speech emotion recognition: E…Deep Learning for Human Affect Recognition: Insights and New Developments (2019)Deep Learning for Human Affec…Speech emotion recognition (2018)Speech emotion recognitionSpeech emotion recognition using deep 1D & 2D CNN LSTM networks (2018)Speech emotion recognition us…Databases, features and classifiers for speech emotion recognition: a review (2018)Databases, features and class…3-D Convolutional Recurrent Neural Networks With Attention Model for Speech Emotion Recognition (2018)3-D Convolutional Recurrent N…Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching (2017)Speech Emotion Recognition Us…Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network (2016)Adieu features? End-to-end sp…High-level feature representation using recurrent neural network for speech emotion recognition (2015)High-level feature representa…Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks (2014)Learning Salient Features for…Emotion recognition from speech: a review (2012)Emotion recognition from spee…Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Survey on speech emotion reco…IEMOCAP: interactive emotional dyadic motion capture database (2008)IEMOCAP: interactive emotiona…A database of German emotional speech (2005)A database of German emotiona…Acoustic profiles in vocal emotion expression. (1996)The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English (2018)Vocal communication of emotion: A review of research paradigms (2003)Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors (2018)Attention, intentions, and the structure of discourse (1986)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Emotion recognition in human-computer interaction (2001)Speech emotion recognition using deep neural network and extreme learning machine (2014)A review of affective computing: From unimodal analysis to multimodal fusion (2017)A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions (2008)Evaluating deep learning architectures for Speech Emotion Recognition (2017)Coefficient Alpha and the Internal Structure of Tests (1951)The Hidden Dimension (1973)Affective Computing (1997)MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations (2019)A Concordance Correlation Coefficient to Evaluate Reproducibility (1989)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)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing (2020)A Comprehensive Review of Speech Emotion Recognition Systems (2021)Dawn of the Transformer Era in Speech Emotion Recognition: Closing the Valence Gap (2023)Practical Bayesian Optimization of Machine Learning Algorithms (2012)Speech Emotion Recognition Using Deep Learning Techniques: A Review (2019)Speech emotion recognition with deep convolutional neural networks (2020)A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition (2019)Speech Emotion Recognition From 3D Log-Mel Spectrograms With Deep Learning Network (2019)Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM (2020)Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models (2021)A systematic review on affective computing: emotion models, databases, and recent advances (2022)
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References

  • 2008IEMOCAP: interactive emotional dyadic motion capture database3,864 cited
  • 2005A database of German emotional speech2,365 cited
  • 2010Survey on speech emotion recognition: Features, classification schemes, and databases2,076 cited
  • 2018Speech emotion recognition using deep 1D & 2D CNN LSTM networks1,044 cited
  • 2016Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network905 cited
  • 2019Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers725 cited
  • 2012Emotion recognition from speech: a review644 cited
  • 2014Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks567 cited
  • 2018Speech emotion recognition547 cited
  • 20183-D Convolutional Recurrent Neural Networks With Attention Model for Speech Emotion Recognition503 cited
  • 2017Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching443 cited
  • 2015High-level feature representation using recurrent neural network for speech emotion recognition406 cited
  • 2018Databases, features and classifiers for speech emotion recognition: a review356 cited
  • 2021CTNet: Conversational Transformer Network for Emotion Recognition

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299 cited
  • 2023Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects256 cited
  • 2019Deep Learning for Human Affect Recognition: Insights and New Developments243 cited
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