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DeepCNN: Spectro‐temporal feature representation for speech emotion recognition
16 references·0 citing·30 second hop
DeepCNN: Spectro‐temporal feature representation for speech emotion recognition (2023)DeepCNN: Spectro‐temporal feature represe…Speech emotion recognition with deep convolutional neural networks (2020)Speech emotion recognition wi…Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM (2020)Clustering-Based Speech Emoti…Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers (2019)Speech emotion recognition: E…Speech emotion recognition using deep 1D & 2D CNN LSTM networks (2018)Speech emotion recognition us…Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching (2017)Speech Emotion Recognition Us…Speech Emotion Recognition from Spectrograms with Deep Convolutional Neural Network (2017)Speech Emotion Recognition fr…Efficient Emotion Recognition from Speech Using Deep Learning on Spectrograms (2017)Efficient Emotion Recognition…Automatic speech emotion recognition using recurrent neural networks with local attention (2017)Automatic speech emotion reco…AVEC 2016 (2016)AVEC 2016Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network (2016)Adieu features? End-to-end sp…The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)The Geneva Minimalistic Acous…Speech emotion recognition using deep neural network and extreme learning machine (2014)Speech emotion recognition us…Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks (2014)Learning Salient Features for…The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism (2013)The INTERSPEECH 2013 computat…IEMOCAP: interactive emotional dyadic motion capture database (2008)IEMOCAP: interactive emotiona…A database of German emotional speech (2005)A database of German emotiona…The phonetic description of voice quality (1980)Acoustic profiles in vocal emotion expression. (1996)A new emotion database: considerations, sources and scope (2000)Using uh and um in spontaneous speaking (2002)Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge (2011)End-to-End Multimodal Emotion Recognition Using Deep Neural Networks (2017)Social Signal Processing (2017)Automated assessment of psychiatric disorders using speech: A systematic review (2020)Coefficient Alpha and the Internal Structure of Tests (1951)The Hidden Dimension (1973)Affective Computing (1997)A review of affective computing: From unimodal analysis to multimodal fusion (2017)MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations (2019)Praat, a system for doing phonetics by computer (2002)Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review (2020)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)A Concordance Correlation Coefficient to Evaluate Reproducibility (1989)Vocal communication of emotion: A review of research paradigms (2003)Practical Bayesian Optimization of Machine Learning Algorithms (2012)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)A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions (2008)A Comprehensive Review of Speech Emotion Recognition Systems (2021)Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics (2024)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)Emotion Recognition from Speech Using wav2vec 2.0 Embeddings (2021)Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations (2023)Multimodal Emotion Recognition with Deep Learning: Advancements, challenges, and future directions (2023)Speech Emotion Recognition Using Deep Learning Techniques: A Review (2019)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 speech2,370 cited
  • 2015The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing1,815 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 network908 cited
  • 2014Speech emotion recognition using deep neural network and extreme learning machine822 cited
  • 2017Automatic speech emotion recognition using recurrent neural networks with local attention769 cited
  • 2013The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism733 cited
  • 2019Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers725 cited
  • 2020Speech emotion recognition with deep convolutional neural networks621 cited
  • 2014Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks567 cited
  • 2016AVEC 2016505 cited
  • 2017Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching443 cited
  • 2017Efficient Emotion Recognition from Speech Using Deep Learning on Spectrograms

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422 cited
  • 2017Speech Emotion Recognition from Spectrograms with Deep Convolutional Neural Network414 cited
  • 2020Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM402 cited
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