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Autoencoder-based Unsupervised Domain Adaptation for Speech Emotion Recognition.

, , , and . IEEE Signal Process. Lett., 21 (9): 1068-1072 (2014)

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Active Learning by Sparse Instance Tracking and Classifier Confidence in Acoustic Emotion Recognition., and . INTERSPEECH, page 362-365. ISCA, (2012)Dynamic Difficulty Awareness Training for Continuous Emotion Prediction., , , and . CoRR, (2018)Semisupervised Autoencoders for Speech Emotion Recognition., , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 26 (1): 31-43 (2018)Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives Review Article., , and . IEEE Comput. Intell. Mag., 14 (2): 68-81 (2019)Implicit Fusion by Joint Audiovisual Training for Emotion Recognition in Mono Modality., , , and . ICASSP, page 5861-5865. IEEE, (2019)Exploring Spatio-Temporal Representations by Integrating Attention-based Bidirectional-LSTM-RNNs and FCNs for Speech Emotion Recognition., , , , , and . INTERSPEECH, page 272-276. ISCA, (2018)Automated Classification of Children's Linguistic versus Non-Linguistic Vocalisations., , , and . INTERSPEECH, page 2588-2592. ISCA, (2018)Can Machine Learning Assist Locating the Excitation of Snore Sound? A Review., , , , , , , and . IEEE J. Biomed. Health Informatics, 25 (4): 1233-1246 (2021)Identifying surgical-mask speech using deep neural networks on low-level aggregation., , , , and . SAC, page 580-585. ACM, (2021)GCFormer: A Graph Convolutional Transformer for Speech Emotion Recognition., , , and . ICMI, page 307-313. ACM, (2023)