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SMILENets: Audio Representation Learning via Neural Knowledge Distillation of Traditional Audio-Feature Extractors.

, , and . ICFSP, page 32-37. IEEE, (2023)

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Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture., , and . ICASSP (1), page 577-580. IEEE, (2004)Discrimination of speech and monophonic singing in continuous audio streams applying multi-layer support vector machines., , and . ICME, page 1655-1658. IEEE Computer Society, (2004)Augment to Prevent: Short-Text Data Augmentation in Deep Learning for Hate-Speech Classification., , and . CIKM, page 991-1000. ACM, (2019)Big Data, Deep Learning - At the Edge of X-Ray Speaker Analysis.. SPECOM, volume 10458 of Lecture Notes in Computer Science, page 20-34. Springer, (2017)Audio onset detection: A wavelet packet based approach with recurrent neural networks., , , , and . IJCNN, page 3585-3591. IEEE, (2014)Seeking the SuperStar: Automatic assessment of perceived singing quality., , , , and . IJCNN, page 1560-1569. IEEE, (2017)Improving generalisation and robustness of acoustic affect recognition., , and . ICMI, page 517-522. ACM, (2012)AVEC 2012: the continuous audio/visual emotion challenge., , , , and . ICMI, page 449-456. ACM, (2012)VCMNet: Weakly Supervised Learning for Automatic Infant Vocalisation Maturity Analysis., , , , and . ICMI, page 205-209. ACM, (2019)A machine learning based system for the automatic evaluation of aphasia speech., , , , and . Healthcom, page 1-6. IEEE, (2017)