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Active Learning for Speech Emotion Recognition Using Deep Neural Network
13 references·0 citing·43 second hop
Active Learning for Speech Emotion Recognition Using Deep Neural Network (2019)Active Learning for Speech Emotion Recogn…Semi-Supervised Speech Emotion Recognition With Ladder Networks (2020)Semi-Supervised Speech Emotio…Curriculum Learning for Speech Emotion Recognition From Crowdsourced Labels (2019)Curriculum Learning for Speec…Study of Dense Network Approaches for Speech Emotion Recognition (2018)Study of Dense Network Approa…Domain Adversarial for Acoustic Emotion Recognition (2018)Domain Adversarial for Acoust…Building Naturalistic Emotionally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings (2017)Building Naturalistic Emotion…Enhanced semi-supervised learning for multimodal emotion recognition (2016)Enhanced semi-supervised lear…Supervised domain adaptation for emotion recognition from speech (2015)Supervised domain adaptation …Facial Action Unit Detection Using Active Learning and an Efficient Non-linear Kernel Approximation (2015)Facial Action Unit Detection …Speech Emotion Recognition Using CNN (2014)Speech Emotion Recognition Us…Building a naturalistic emotional speech corpus by retrieving expressive behaviors from existing speech corpora (2014)Building a naturalistic emoti…The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism (2013)The INTERSPEECH 2013 computat…Using multiple databases for training in emotion recognition: to unite or to vote? (2011)Using multiple databases for …Unsupervised learning in cross-corpus acoustic emotion recognition (2011)Unsupervised learning in cros…Measuring emotion: The self-assessment manikin and the semantic differential (1994)The World of Emotions is not Two-Dimensional (2007)IEMOCAP: interactive emotional dyadic motion capture database (2008)On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks (2018)EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion Recognition (2021)Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition (2022)The eNTERFACE’05 Audio-Visual Emotion Database (2006)The Vera am Mittag German audio-visual emotional speech database (2008)Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge (2011)Towards a Small Set of Robust Acoustic Features for Emotion Recognition: Challenges (2015)Cross Lingual Speech Emotion Recognition: Urdu vs. Western Languages (2018)A database of German emotional speech (2005)The Singularity is Near (2014)Deep Learning for Human Affect Recognition: Insights and New Developments (2019)Speech Emotion Recognition From 3D Log-Mel Spectrograms With Deep Learning Network (2019)A Review on Speech Emotion Recognition Using Deep Learning and Attention Mechanism (2021)Using uh and um in spontaneous speaking (2002)AVEC 2016 (2016)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)The INTERSPEECH 2009 emotion challenge (2009)Human–Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention (2023)Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010)Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions (2013)Continuous Estimation of Emotions in Speech by Dynamic Cooperative Speaker Models (2016)Strength modelling for real-worldautomatic continuous affect recognition from audiovisual signals (2016)The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)Emotion recognition from unimodal to multimodal analysis: A review (2023)Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies (2010)MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception (2016)A survey of speech emotion recognition in natural environment (2020)Survey of Deep Representation Learning for Speech Emotion Recognition (2021)Automated emotion recognition: Current trends and future perspectives (2022)Emotional intelligence meets traditional standards for an intelligence (1999)Applications of Item Response Theory To Practical Testing Problems (2012)Dynamic Difficulty Awareness Training for Continuous Emotion Prediction (2018)EmoBed: Strengthening Monomodal Emotion Recognition via Training with Crossmodal Emotion Embeddings (2019)Multi-Classifier Interactive Learning for Ambiguous Speech Emotion Recognition (2022)A review of depression and suicide risk assessment using speech analysis (2015)Spatiotemporal and frequential cascaded attention networks for speech emotion recognition (2021)Speech Emotion Recognition with Multiscale Area Attention and Data Augmentation (2021)Speech Emotion Recognition Using Attention Model (2023)
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References

  • 2013The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism733 cited
  • 2014Speech Emotion Recognition Using CNN416 cited
  • 2017Building Naturalistic Emotionally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings331 cited
  • 2018Domain Adversarial for Acoustic Emotion Recognition178 cited
  • 2011Unsupervised learning in cross-corpus acoustic emotion recognition124 cited
  • 2020Semi-Supervised Speech Emotion Recognition With Ladder Networks119 cited
  • 2019Curriculum Learning for Speech Emotion Recognition From Crowdsourced Labels97 cited
  • 2015Supervised domain adaptation for emotion recognition from speech80 cited
  • 2011Using multiple databases for training in emotion recognition: to unite or to vote?76 cited
  • 2016Enhanced semi-supervised learning for multimodal emotion recognition72 cited
  • 2015Facial Action Unit Detection Using Active Learning and an Efficient Non-linear Kernel Approximation59 cited
  • 2014Building a naturalistic emotional speech corpus by retrieving expressive behaviors from existing speech corpora53 cited
  • 2018Study of Dense Network Approaches for Speech Emotion Recognition53 cited

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